2026
Journal article
Open Access
Evaluation of underfloor accelerometers for enabling location-based services in intelligent environments
Belli Dimitri, Crivello Antonino, La Rosa Davide, Barsocchi Paolo
Device-free indoor localization systems play a pivotal role in enhancing the functionality and intelligence of modern environments. They can effectively monitor people’s movements in their everyday environment without the constraints of invasive or wearable devices, and are open to a wide range of application domains. Through a systematic experimental approach, in this work we investigate the performance of underfloor accelerometers in accurately detecting and tracking user movements. The collected data, augmented with ground truth information, are analyzed using fingerprint maps and k-Nearest Neighbor (k-NN) algorithms to estimate the user’s position within the environment. In the literature, this work represents a first attempt to apply the fingerprint technique in this context. The results show promising capabilities of underfloor accelerometers in facilitating location-based services, while the short time required for installation, data pre-processing and calibration indicate this approach as an easy-to-deploy location-based system. In this regard, intra-user tests show that the variability of the error exceeds 1 m regardless of k-values or time windows, inter-user tests show that the time window does not affect the variability of distance estimation with 2-NN, which outperforms other k-configurations, while 3-NN performs better as the time window increases. The cumulative distribution function over the entire test set shows that more than 75% of the predictions are less than 1 m.Source: INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS, vol. 19 (issue 1)
DOI: 10.1007/s44196-026-01205-2
Project(s): PE8 - Conseguenze e sfide dell'invecchiamento
Metrics:
Belli Dimitri, Crivello Antonino, La Rosa Davide, Barsocchi Paolo
Device-free indoor localization systems play a pivotal role in enhancing the functionality and intelligence of modern environments. They can effectively monitor people’s movements in their everyday environment without the constraints of invasive or wearable devices, and are open to a wide range of application domains. Through a systematic experimental approach, in this work we investigate the performance of underfloor accelerometers in accurately detecting and tracking user movements. The collected data, augmented with ground truth information, are analyzed using fingerprint maps and k-Nearest Neighbor (k-NN) algorithms to estimate the user’s position within the environment. In the literature, this work represents a first attempt to apply the fingerprint technique in this context. The results show promising capabilities of underfloor accelerometers in facilitating location-based services, while the short time required for installation, data pre-processing and calibration indicate this approach as an easy-to-deploy location-based system. In this regard, intra-user tests show that the variability of the error exceeds 1 m regardless of k-values or time windows, inter-user tests show that the time window does not affect the variability of distance estimation with 2-NN, which outperforms other k-configurations, while 3-NN performs better as the time window increases. The cumulative distribution function over the entire test set shows that more than 75% of the predictions are less than 1 m.Source: INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS, vol. 19 (issue 1)
DOI: 10.1007/s44196-026-01205-2
Project(s): PE8 - Conseguenze e sfide dell'invecchiamento
Metrics:
See at:
CNR IRIS 
| link.springer.com | CNR IRIS 
2026
Journal article
Open Access
Effectiveness of changing stimulus frequency and intensity of sound for evaluating hearing by monitoring pupil responses
Tramonti Fantozzi Mara Paola, Crivello Antonino, La Rosa Davide, Marconi Ottavia, Milazzo Mario, Manzoni Diego, Fiacchini Giacomo, Bruschini Luca
Assessing hearing through the pupil dilation response (PDR) to sound offers a non-invasive alternative to traditional audiometry, particularly useful in individuals unable to provide behavioral responses. However, reliable detection of sound-evoked PDRs is limited by variability in pupil size and the risk of false positives (Type I Errors). This study investigated whether pseudo-random variation of sound frequency and amplitude enhances the correspondence between PDR detection and sound perception in normal-hearing subjects. To improve reliability, epochs with different pre-stimulus pupil sizes were analyzed separately, as baseline pupil diameter affects PDR amplitude. Pupil responses to auditory stimuli were recorded, averaged, and compared with baseline data obtained in silence. Additional averages were computed for specific frequencies, amplitudes, and pre-stimulus pupil size ranges. Sub-threshold PDR traces were further processed by averaging all possible differences between sound and baseline frames. The probability of Type I Errors was estimated using randomly sampled baseline data. Results show that using stimuli with varying frequency and amplitude markedly increased PDR retrieval compared with standard constant-tone paradigms. Restricting analysis to defined pre-stimulus pupil size ranges or specific stimulus parameters further improved detection rates. The difference-averaging method confirmed several low-amplitude PDRs as genuine responses, though some may still occur by chance. Overall, significant PDRs were observed in 80% of participants, indicating that while this approach enhances sensitivity, further refinement is needed before clinical application. More efficient paradigms are required to establish reliable, objective hearing assessment “by looking into the eyes.”Source: BIOMEDICAL SIGNAL PROCESSING AND CONTROL, vol. 120-A (issue 110035)
DOI: 10.1016/j.bspc.2026.110035
Project(s): Audiometry with Pupil Response
Metrics:
Tramonti Fantozzi Mara Paola, Crivello Antonino, La Rosa Davide, Marconi Ottavia, Milazzo Mario, Manzoni Diego, Fiacchini Giacomo, Bruschini Luca
Assessing hearing through the pupil dilation response (PDR) to sound offers a non-invasive alternative to traditional audiometry, particularly useful in individuals unable to provide behavioral responses. However, reliable detection of sound-evoked PDRs is limited by variability in pupil size and the risk of false positives (Type I Errors). This study investigated whether pseudo-random variation of sound frequency and amplitude enhances the correspondence between PDR detection and sound perception in normal-hearing subjects. To improve reliability, epochs with different pre-stimulus pupil sizes were analyzed separately, as baseline pupil diameter affects PDR amplitude. Pupil responses to auditory stimuli were recorded, averaged, and compared with baseline data obtained in silence. Additional averages were computed for specific frequencies, amplitudes, and pre-stimulus pupil size ranges. Sub-threshold PDR traces were further processed by averaging all possible differences between sound and baseline frames. The probability of Type I Errors was estimated using randomly sampled baseline data. Results show that using stimuli with varying frequency and amplitude markedly increased PDR retrieval compared with standard constant-tone paradigms. Restricting analysis to defined pre-stimulus pupil size ranges or specific stimulus parameters further improved detection rates. The difference-averaging method confirmed several low-amplitude PDRs as genuine responses, though some may still occur by chance. Overall, significant PDRs were observed in 80% of participants, indicating that while this approach enhances sensitivity, further refinement is needed before clinical application. More efficient paradigms are required to establish reliable, objective hearing assessment “by looking into the eyes.”Source: BIOMEDICAL SIGNAL PROCESSING AND CONTROL, vol. 120-A (issue 110035)
DOI: 10.1016/j.bspc.2026.110035
Project(s): Audiometry with Pupil Response
Metrics:
See at:
Biomedical Signal Processing and Control | CNR IRIS | www.sciencedirect.com | CNR IRIS
2025
Journal article
Open Access
An experimental dataset using UAVs and LoRa technology in avalanche scenarios
Mavilia F., La Rosa D., Berton A., Girolami M.
Wireless communication technologies play a critical role in the effectiveness of Search and Rescue (SaR) operations, especially in avalanche scenarios where rapid localization of victims is essential. Traditional systems like ARTVA research beacons have been widely adopted for this purpose, but their performance is strongly affected by environmental factors such as snow depth and snowpack characteristics. The dataset presented in this article explores the feasibility and the performance of LoRa (Long Range) technology on board of a UAV for use in SaR scenarios. The transmitter was buried in snow across a wide area in the Dolomites, simulating the scale and conditions of a typical human-triggered avalanche, while the receiver is mounted on a commercial UAV following different flight trajectories. Specifically, we vary the flying path, duration, covered area and antenna type. For each experiment, we record key communication metrics such as the Received Signal Strength Indicator (RSSI) and the Signal-to-Noise Ratio (SNR), together with precise ground truth transmitter and receiver positions obtained via GPS-RTK. The tests covered both dry and wet snow conditions, allowing evaluation of how snow characteristics impact LoRa performance. This dataset provides strong reuse potential for researchers aiming to improve UAV-assisted localization algorithms in extreme snow environments. It can support the development and benchmarking of positioning methods based on LoRa signal strength and, more broadly, the design of resilient SaR communication systems for avalanche-prone areasBy releasing the data and contextual documentation publicly, we seek to encourage innovation in disaster response technologies and promote safer mountain rescue practices.Source: DATA IN BRIEF, vol. 63 (issue 112243)
DOI: 10.1016/j.dib.2025.112243
Metrics:
Mavilia F., La Rosa D., Berton A., Girolami M.
Wireless communication technologies play a critical role in the effectiveness of Search and Rescue (SaR) operations, especially in avalanche scenarios where rapid localization of victims is essential. Traditional systems like ARTVA research beacons have been widely adopted for this purpose, but their performance is strongly affected by environmental factors such as snow depth and snowpack characteristics. The dataset presented in this article explores the feasibility and the performance of LoRa (Long Range) technology on board of a UAV for use in SaR scenarios. The transmitter was buried in snow across a wide area in the Dolomites, simulating the scale and conditions of a typical human-triggered avalanche, while the receiver is mounted on a commercial UAV following different flight trajectories. Specifically, we vary the flying path, duration, covered area and antenna type. For each experiment, we record key communication metrics such as the Received Signal Strength Indicator (RSSI) and the Signal-to-Noise Ratio (SNR), together with precise ground truth transmitter and receiver positions obtained via GPS-RTK. The tests covered both dry and wet snow conditions, allowing evaluation of how snow characteristics impact LoRa performance. This dataset provides strong reuse potential for researchers aiming to improve UAV-assisted localization algorithms in extreme snow environments. It can support the development and benchmarking of positioning methods based on LoRa signal strength and, more broadly, the design of resilient SaR communication systems for avalanche-prone areasBy releasing the data and contextual documentation publicly, we seek to encourage innovation in disaster response technologies and promote safer mountain rescue practices.Source: DATA IN BRIEF, vol. 63 (issue 112243)
DOI: 10.1016/j.dib.2025.112243
Metrics:
See at:
CNR IRIS | www.sciencedirect.com | CNR IRIS | CNR IRIS
2025
Journal article
Open Access
Challenges in using pupil dilation responses to sounds as a reliable alternative to standard audiometric tests
Tramonti Fantozzi M. P., Crivello A., La Rosa D., Milazzo M., Danti S., De Cicco V., Orsini P., Manzoni D., Lazzerini F., Canelli R., Fiacchini G., Bruschini L.
Assessing hearing in neonates and uncooperative patients can be challenging. Pupil dilation response (PDR) as an objective physiological measure may offer a solution. To test its feasibility, PDRs were averaged in response to a sequence of 60–100 audible tones (same frequency and amplitude). This was performed in subjects with normal hearing and communication abilities, who were exposed to two different lighting levels. We evaluated whether averaged post-stimulus intervals of PDRs were significantly different from randomly generated averages of pupil traces recorded in the absence of sound stimulation from the same subject. This analysis was repeated for the first, second, and third block of PDRs to account for possible adaptation phenomena. Although all the participants clearly perceived the tones, significant PDRs in response to sound were only detected in a fraction of subjects, primarily in the low luminance condition. Consequently, only in the low luminance group, the grand average of individual PDRs was significantly larger than that obtained for traces recorded in the absence of sound input. In this most favorable condition, when the three blocks of PDRs were averaged separately, significant PDRs were observed in 40 % of the subjects in at least one of the blocks. Therefore, the PDR to sound input is not a reliable indicator of hearing perception when standard audiometric stimuli of the same amplitude and frequency are used. Possible modifications to sound input and stimulation protocols for obtaining reliable PDRs in diagnosing and treating hearing impairments are discussed.Source: HELIYON, vol. 11 (issue 4)
DOI: 10.1016/j.heliyon.2025.e42666
Project(s): APURE - Audiometry with PUpil REsponse
Metrics:
Tramonti Fantozzi M. P., Crivello A., La Rosa D., Milazzo M., Danti S., De Cicco V., Orsini P., Manzoni D., Lazzerini F., Canelli R., Fiacchini G., Bruschini L.
Assessing hearing in neonates and uncooperative patients can be challenging. Pupil dilation response (PDR) as an objective physiological measure may offer a solution. To test its feasibility, PDRs were averaged in response to a sequence of 60–100 audible tones (same frequency and amplitude). This was performed in subjects with normal hearing and communication abilities, who were exposed to two different lighting levels. We evaluated whether averaged post-stimulus intervals of PDRs were significantly different from randomly generated averages of pupil traces recorded in the absence of sound stimulation from the same subject. This analysis was repeated for the first, second, and third block of PDRs to account for possible adaptation phenomena. Although all the participants clearly perceived the tones, significant PDRs in response to sound were only detected in a fraction of subjects, primarily in the low luminance condition. Consequently, only in the low luminance group, the grand average of individual PDRs was significantly larger than that obtained for traces recorded in the absence of sound input. In this most favorable condition, when the three blocks of PDRs were averaged separately, significant PDRs were observed in 40 % of the subjects in at least one of the blocks. Therefore, the PDR to sound input is not a reliable indicator of hearing perception when standard audiometric stimuli of the same amplitude and frequency are used. Possible modifications to sound input and stimulation protocols for obtaining reliable PDRs in diagnosing and treating hearing impairments are discussed.Source: HELIYON, vol. 11 (issue 4)
DOI: 10.1016/j.heliyon.2025.e42666
Project(s): APURE - Audiometry with PUpil REsponse
Metrics:
See at:
Heliyon | Archivio della Ricerca - Università di Pisa | CNR IRIS | Heliyon | www.sciencedirect.com | Archivio della Ricerca - Università di Pisa | CNR IRIS
2025
Conference article
Open Access
Multisensor setup for functional capacity testing: the Malisa Dataset
Salvi D, Magnus Olsson C., Lamrani Laghrib H., Merle K., Pothier Noa, Yildirim S., La Rosa D., Palumbo F.
Functional capacity testing is essential for assessing mobility changes, which can impact independence across various populations and health conditions. This study aims to implement instrumented function tests using a combination of affordable sensors, including sensorized mats, sensorized shoes, smartphones, and smartwatches. The goal is to provide objective, reliable, and detailed data on test outcomes, such as gait analysis. We have created a dataset from 6 participants of varying ages, each performing 5 standardized functional tests: Timed Up and Go, 30-Second Chair Rise, Locomo challenge, 10-meter walk, and 40-meter walk. Alongside the dataset, we have developed a tool for visualizing the sensor signals and marking key events to facilitate data analysis. This dataset is intended to support researchers in developing algorithms for extracting test-specific parameters, and for comparing sensors in terms of quality of the signals and ease of setup.Source: LECTURE NOTES OF THE INSTITUTE FOR COMPUTER SCIENCES, SOCIAL INFORMATICS AND TELECOMMUNICATIONS ENGINEERING (INTERNET), vol. 612, pp. 170-178. Heraklion, Crete, Greece, 17-18/09/2024
DOI: 10.1007/978-3-031-85575-7_10
DOI: https://doi.org/10.1007/978-3-031-85575-7_10
Metrics:
Salvi D, Magnus Olsson C., Lamrani Laghrib H., Merle K., Pothier Noa, Yildirim S., La Rosa D., Palumbo F.
Functional capacity testing is essential for assessing mobility changes, which can impact independence across various populations and health conditions. This study aims to implement instrumented function tests using a combination of affordable sensors, including sensorized mats, sensorized shoes, smartphones, and smartwatches. The goal is to provide objective, reliable, and detailed data on test outcomes, such as gait analysis. We have created a dataset from 6 participants of varying ages, each performing 5 standardized functional tests: Timed Up and Go, 30-Second Chair Rise, Locomo challenge, 10-meter walk, and 40-meter walk. Alongside the dataset, we have developed a tool for visualizing the sensor signals and marking key events to facilitate data analysis. This dataset is intended to support researchers in developing algorithms for extracting test-specific parameters, and for comparing sensors in terms of quality of the signals and ease of setup.Source: LECTURE NOTES OF THE INSTITUTE FOR COMPUTER SCIENCES, SOCIAL INFORMATICS AND TELECOMMUNICATIONS ENGINEERING (INTERNET), vol. 612, pp. 170-178. Heraklion, Crete, Greece, 17-18/09/2024
DOI: 10.1007/978-3-031-85575-7_10
DOI: https://doi.org/10.1007/978-3-031-85575-7_10
Metrics:
2025
Journal article
Open Access
Beyond prototypes: what is missing to fill the gaps in IoT-enabled hydroponics platforms
Sportelli M., La Rosa D., Crivello A., Pineda-Medina Dunia, Bacco M., Barsocchi P.
Hydroponic agriculture, when combined with Internet of Things (IoT) technologies, provides a promising pathway to sustainable and efficient food production. This paper aims to systematically review and analyze recent advancements in IoT-based management for hydroponic systems, with a particular focus on assessing the technological maturity of current solutions, identifying existing gaps, and outlining promising directions for future research and development. Based on a review of 74 recent studies, the findings reveal a fragmented landscape characterized by custom-built solutions, predominantly relying on open-source microcontrollers and WiFi connectivity, but with limited adoption of standardized protocols and interoperable platforms. The majority of applications emphasize monitoring of core hydroponic parameters such as pH, EC, and temperature, while emerging uses of machine learning remain at an early stage. Few systems demonstrate readiness for commercial deployment or integration within broader smart agriculture ecosystems. By clarifying the current state of IoT-enabled hydroponics, this review highlights both the opportunities and the challenges in advancing from isolated prototypes toward robust, scalable systems capable of real-world application.Source: HORTICULTURAE, vol. 11 (issue 11)
DOI: 10.3390/horticulturae11111322
Metrics:
Sportelli M., La Rosa D., Crivello A., Pineda-Medina Dunia, Bacco M., Barsocchi P.
Hydroponic agriculture, when combined with Internet of Things (IoT) technologies, provides a promising pathway to sustainable and efficient food production. This paper aims to systematically review and analyze recent advancements in IoT-based management for hydroponic systems, with a particular focus on assessing the technological maturity of current solutions, identifying existing gaps, and outlining promising directions for future research and development. Based on a review of 74 recent studies, the findings reveal a fragmented landscape characterized by custom-built solutions, predominantly relying on open-source microcontrollers and WiFi connectivity, but with limited adoption of standardized protocols and interoperable platforms. The majority of applications emphasize monitoring of core hydroponic parameters such as pH, EC, and temperature, while emerging uses of machine learning remain at an early stage. Few systems demonstrate readiness for commercial deployment or integration within broader smart agriculture ecosystems. By clarifying the current state of IoT-enabled hydroponics, this review highlights both the opportunities and the challenges in advancing from isolated prototypes toward robust, scalable systems capable of real-world application.Source: HORTICULTURAE, vol. 11 (issue 11)
DOI: 10.3390/horticulturae11111322
Metrics:
See at:
Horticulturae | CNR IRIS | www.mdpi.com | CNR IRIS
2025
Conference article
Open Access
Objective characterization of timed up and go test via sensorized mats
Eriksson H., Ramkull M., Salvi D., Magnus Olsson C., Ghezzi D., La Rosa D., Palumbo F.
The Timed Up and Go (TUG) test is a widely recognized and standardized mobility test to measure basic mobility and balance capabilities. Despite the possibility to derive rich information about the patient, only the total time to complete the test is conventionally measured by a professional. This work examines the use of non-wearable sensors for the measurement of parameters of the test in an accurate and objective way. The study illustrates a system specifically designed for conducting the TUG test using a set of sensorized mats. The developed system is able to identify the following 4 phases of the test, with relative timestamps: TUG-time, Sit-to-Stand, Mid-Turning, and End-Turning-Stand-to-Sit. Additionally, meaningful parameters for gait assessment are also extracted: walking speed and stride length. Two experimental iterations were conducted to assess the reliability of the developed software. Both iterations involved two different groups of six healthy participants (41.58 ± 13.32 yrs; 6 females, 6 males) performing various walking types. Our results demonstrate that sensorized mats can be used to segment the phases of the test reliably and can additionally be used to quantify gait parameters during the walk phase of the test.Source: LECTURE NOTES OF THE INSTITUTE FOR COMPUTER SCIENCES, SOCIAL INFORMATICS AND TELECOMMUNICATIONS ENGINEERING, vol. 612, pp. 179-189. Heraklion, Crete, Greece, 17-18/09/2024
DOI: 10.1007/978-3-031-85575-7_11
DOI: https://doi.org/10.1007/978-3-031-85575-7_11
Metrics:
Eriksson H., Ramkull M., Salvi D., Magnus Olsson C., Ghezzi D., La Rosa D., Palumbo F.
The Timed Up and Go (TUG) test is a widely recognized and standardized mobility test to measure basic mobility and balance capabilities. Despite the possibility to derive rich information about the patient, only the total time to complete the test is conventionally measured by a professional. This work examines the use of non-wearable sensors for the measurement of parameters of the test in an accurate and objective way. The study illustrates a system specifically designed for conducting the TUG test using a set of sensorized mats. The developed system is able to identify the following 4 phases of the test, with relative timestamps: TUG-time, Sit-to-Stand, Mid-Turning, and End-Turning-Stand-to-Sit. Additionally, meaningful parameters for gait assessment are also extracted: walking speed and stride length. Two experimental iterations were conducted to assess the reliability of the developed software. Both iterations involved two different groups of six healthy participants (41.58 ± 13.32 yrs; 6 females, 6 males) performing various walking types. Our results demonstrate that sensorized mats can be used to segment the phases of the test reliably and can additionally be used to quantify gait parameters during the walk phase of the test.Source: LECTURE NOTES OF THE INSTITUTE FOR COMPUTER SCIENCES, SOCIAL INFORMATICS AND TELECOMMUNICATIONS ENGINEERING, vol. 612, pp. 179-189. Heraklion, Crete, Greece, 17-18/09/2024
DOI: 10.1007/978-3-031-85575-7_11
DOI: https://doi.org/10.1007/978-3-031-85575-7_11
Metrics:
2025
Journal article
Open Access
MCSim: A multi-access edge computing mobile crowdsensing simulator
Belli D., Barsocchi P., Crivello A., La Rosa D., Girolami M.
This paper introduces MCSim, a modular and extensible simulator designed to support the planning and evaluation of Mobile CrowdSensing (MCS) campaigns in urban environments. MCSim integrates a useful approximation of urban mobility patterns based on real-world street networks, as well as the simulation of task execution effectiveness within configurable data transmission ranges. Unlike other simulators, MCSim is built to accommodate future extensions, such as edge/fog computing architectures. The current version of the software offers a user-friendly interface, customizable configuration options, and robust output analysis. By combining realistic mobility modeling, configurable task logic, and architectural flexibility, MCSim provides researchers and practitioners with a powerful tool for optimizing MCS strategies while minimizing deployment costs and risks.Source: SOFTWAREX, vol. 31 (issue 102229)
DOI: 10.1016/j.softx.2025.102229
Project(s): Cyber and Human Intelligence for Physical Systems
Metrics:
Belli D., Barsocchi P., Crivello A., La Rosa D., Girolami M.
This paper introduces MCSim, a modular and extensible simulator designed to support the planning and evaluation of Mobile CrowdSensing (MCS) campaigns in urban environments. MCSim integrates a useful approximation of urban mobility patterns based on real-world street networks, as well as the simulation of task execution effectiveness within configurable data transmission ranges. Unlike other simulators, MCSim is built to accommodate future extensions, such as edge/fog computing architectures. The current version of the software offers a user-friendly interface, customizable configuration options, and robust output analysis. By combining realistic mobility modeling, configurable task logic, and architectural flexibility, MCSim provides researchers and practitioners with a powerful tool for optimizing MCS strategies while minimizing deployment costs and risks.Source: SOFTWAREX, vol. 31 (issue 102229)
DOI: 10.1016/j.softx.2025.102229
Project(s): Cyber and Human Intelligence for Physical Systems
Metrics:
See at:
SoftwareX | SoftwareX | CNR IRIS | www.sciencedirect.com | CNR IRIS | CNR IRIS
2025
Conference article
Open Access
Performing audiometry using pupillometry: state-of-the-market and sensor selection
Crivello A., La Rosa D., Belli D., Milazzo M., Palumbo F.
Hearing impairment poses a significant global health challenge, impacting millions of individuals across all age groups. Early detection and intervention are paramount, especially in infants and young children, to mitigate the adverse effects on speech, language, and cognitive development. Traditional audiometry methods, however, rely on subjective patient responses, rendering them unsuitable for non-collaborative individuals such as infants, newborns, and those with cognitive impairments. To address this limitation, the APURE (Audiometry with PUpil REsponse) project seeks to develop an objective audiometer leveraging pupillometry, the measurement of pupil size and reactivity. This paper presents a comprehensive state-of-the-market survey of eye-tracking systems, a crucial step in identifying the most suitable sensors for the APURE project.Source: LECTURE NOTES OF THE INSTITUTE FOR COMPUTER SCIENCES, SOCIAL INFORMATICS AND TELECOMMUNICATIONS ENGINEERING, vol. 612, pp. 159-169. Heraklion, Crete, Greece, 17–18/09/2024
DOI: 10.1007/978-3-031-85575-7_9
Metrics:
Crivello A., La Rosa D., Belli D., Milazzo M., Palumbo F.
Hearing impairment poses a significant global health challenge, impacting millions of individuals across all age groups. Early detection and intervention are paramount, especially in infants and young children, to mitigate the adverse effects on speech, language, and cognitive development. Traditional audiometry methods, however, rely on subjective patient responses, rendering them unsuitable for non-collaborative individuals such as infants, newborns, and those with cognitive impairments. To address this limitation, the APURE (Audiometry with PUpil REsponse) project seeks to develop an objective audiometer leveraging pupillometry, the measurement of pupil size and reactivity. This paper presents a comprehensive state-of-the-market survey of eye-tracking systems, a crucial step in identifying the most suitable sensors for the APURE project.Source: LECTURE NOTES OF THE INSTITUTE FOR COMPUTER SCIENCES, SOCIAL INFORMATICS AND TELECOMMUNICATIONS ENGINEERING, vol. 612, pp. 159-169. Heraklion, Crete, Greece, 17–18/09/2024
DOI: 10.1007/978-3-031-85575-7_9
Metrics:
See at:
CNR IRIS | link.springer.com | CNR IRIS | CNR IRIS
2024
Conference article
Open Access
A novel architectural schema for constant monitoring and assessment of older adults’ health status at home
Barsocchi P., Belli D., Gabrielli E., La Rosa D., Miori V., Palumbo F., Russo D., Tolomei G.
In recent years the demand for health care among older adults, along with requests for hospitalization and related costs, has increased at an unprecedented rate. In the coming decades, this trend is likely to worsen. This detrimental tendency can be mitigated by addressing the problem with a proactive approach. The goal is to ensure continuous monitoring of the older’s health status to promptly detect worsening and disease onsets. The paper extends the mid-term results of the Project ChAALenge, by detailing the sensors and the framework underlying the high-level predictive techniques, as well as by reporting qualitative results in terms of physiological measurements from a 4-month data collection campaign in a nursing home.Source: LECTURE NOTES OF THE INSTITUTE FOR COMPUTER SCIENCES, SOCIAL INFORMATICS AND TELECOMMUNICATIONS ENGINEERING, vol. 572, pp. 501-511. Malmö, Sweden, 27-29/11/2023
DOI: 10.1007/978-3-031-59717-6_33
Metrics:
Barsocchi P., Belli D., Gabrielli E., La Rosa D., Miori V., Palumbo F., Russo D., Tolomei G.
In recent years the demand for health care among older adults, along with requests for hospitalization and related costs, has increased at an unprecedented rate. In the coming decades, this trend is likely to worsen. This detrimental tendency can be mitigated by addressing the problem with a proactive approach. The goal is to ensure continuous monitoring of the older’s health status to promptly detect worsening and disease onsets. The paper extends the mid-term results of the Project ChAALenge, by detailing the sensors and the framework underlying the high-level predictive techniques, as well as by reporting qualitative results in terms of physiological measurements from a 4-month data collection campaign in a nursing home.Source: LECTURE NOTES OF THE INSTITUTE FOR COMPUTER SCIENCES, SOCIAL INFORMATICS AND TELECOMMUNICATIONS ENGINEERING, vol. 572, pp. 501-511. Malmö, Sweden, 27-29/11/2023
DOI: 10.1007/978-3-031-59717-6_33
Metrics:
See at:
CNR IRIS | link.springer.com | doi.org | Archivio della ricerca- Università di Roma La Sapienza | CNR IRIS | CNR IRIS
2024
Conference article
Open Access
An IoT Platform for smart hydroponics: building blocks and open challenges
Sportelli M., Crivello A., La Rosa D., Bacco M., Incrocci L., Barsocchi P.
Hydroponics addresses inefficiencies in traditional soil-based farming by optimizing water, nutrients, and pesticide use. This method has the potential to boost crop yields and significantly reduce water consumption, tackling issues of inefficient irrigation and fertilization. This study presents the development of an IoT-based platform designed to optimize the management of smart hydroponic systems. The proposed platform facilitates real-time monitoring of key environmental parameters for hydroponic farming as well as automatic regulation of greenhouse conditions, such as temperature, humidity and nutrient levels. The platform leverages middleware software to ensure seamless communication and data management, enabling efficient decision-making processes. The primary aim of this work is to enhance the productivity and efficiency of hydroponic systems through a scalable and user-friendly solution by integrating different sensors and actuators that could be accessible through both web and mobile applications. The platform's open and flexible architecture supports the integration of advanced sensing technologies and artificial intelligence, contributing to the digitalization of agriculture and promoting environmental sustainability.DOI: 10.1109/metroagrifor63043.2024.10948780
Project(s): CODECS
Metrics:
Sportelli M., Crivello A., La Rosa D., Bacco M., Incrocci L., Barsocchi P.
Hydroponics addresses inefficiencies in traditional soil-based farming by optimizing water, nutrients, and pesticide use. This method has the potential to boost crop yields and significantly reduce water consumption, tackling issues of inefficient irrigation and fertilization. This study presents the development of an IoT-based platform designed to optimize the management of smart hydroponic systems. The proposed platform facilitates real-time monitoring of key environmental parameters for hydroponic farming as well as automatic regulation of greenhouse conditions, such as temperature, humidity and nutrient levels. The platform leverages middleware software to ensure seamless communication and data management, enabling efficient decision-making processes. The primary aim of this work is to enhance the productivity and efficiency of hydroponic systems through a scalable and user-friendly solution by integrating different sensors and actuators that could be accessible through both web and mobile applications. The platform's open and flexible architecture supports the integration of advanced sensing technologies and artificial intelligence, contributing to the digitalization of agriculture and promoting environmental sustainability.DOI: 10.1109/metroagrifor63043.2024.10948780
Project(s): CODECS
Metrics:
See at:
CNR IRIS | ieeexplore.ieee.org | doi.org | CNR IRIS
2024
Journal article
Open Access
Pupil data upon stimulation by auditory stimuli
Davide La Rosa, Luca Bruschini, Maria Paola Tramonti Fantozzi, Paolo Orsini, Mario Milazzo, Antonino Crivello
Source: DATA, vol. 9 (issue 3)
DOI: 10.3390/data9030043
Project(s): Apure - Audiometry with pupil response
Metrics:
Davide La Rosa, Luca Bruschini, Maria Paola Tramonti Fantozzi, Paolo Orsini, Mario Milazzo, Antonino Crivello
Source: DATA, vol. 9 (issue 3)
DOI: 10.3390/data9030043
Project(s): Apure - Audiometry with pupil response
Metrics:
See at:
Data | IRIS Cnr | IRIS Cnr | IRIS Cnr | Archivio della Ricerca - Università di Pisa | Archivio della Ricerca - Università di Pisa | CNR IRIS
2024
Journal article
Open Access
Bluetooth dataset for proximity detection in indoor environments collected with smartphones
Girolami M., La Rosa D., Barsocchi P.
This paper describes a data collection experiment and the resulting dataset based on Bluetooth beacon messages collected in an indoor museum. The goal of this dataset is to study algorithms and techniques for proximity detection between people and points of interest (POI). To this purpose, we release the data we collected during 32 museum's visits, in which we vary the adopted smartphones and the visiting paths. The smartphone is used to collect Bluetooth beacons emitted by Bluetooth tags positioned nearby each POI. The visiting layout defines the order of visit of 10 artworks. The combination of different smartphones, the visiting paths and features of the indoor museum allow experiencing with realistic environmental conditions. The dataset comprises RSS (Received Signal Strength) values, timestamp and artwork identifiers, as long as a detailed ground truth, reporting the starting and ending time of each artwork's visit. The dataset is addressed to researchers and industrial players interested in further investigating how to automatically detect the location or the proximity between people and specific points of interest, by exploiting commercial technologies available with smartphone. The dataset is designed to speed up the prototyping process, by releasing an accurate ground truth annotation and details concerning the adopted hardware.Source: DATA IN BRIEF, vol. 53
DOI: 10.1016/j.dib.2024.110215
Project(s): Project Tuscany Health Ecosystem, Recupero di Sistemi Informativi STOrico-artistici per una rinnovata comunicazione del patrimonio
Metrics:
Girolami M., La Rosa D., Barsocchi P.
This paper describes a data collection experiment and the resulting dataset based on Bluetooth beacon messages collected in an indoor museum. The goal of this dataset is to study algorithms and techniques for proximity detection between people and points of interest (POI). To this purpose, we release the data we collected during 32 museum's visits, in which we vary the adopted smartphones and the visiting paths. The smartphone is used to collect Bluetooth beacons emitted by Bluetooth tags positioned nearby each POI. The visiting layout defines the order of visit of 10 artworks. The combination of different smartphones, the visiting paths and features of the indoor museum allow experiencing with realistic environmental conditions. The dataset comprises RSS (Received Signal Strength) values, timestamp and artwork identifiers, as long as a detailed ground truth, reporting the starting and ending time of each artwork's visit. The dataset is addressed to researchers and industrial players interested in further investigating how to automatically detect the location or the proximity between people and specific points of interest, by exploiting commercial technologies available with smartphone. The dataset is designed to speed up the prototyping process, by releasing an accurate ground truth annotation and details concerning the adopted hardware.Source: DATA IN BRIEF, vol. 53
DOI: 10.1016/j.dib.2024.110215
Project(s): Project Tuscany Health Ecosystem, Recupero di Sistemi Informativi STOrico-artistici per una rinnovata comunicazione del patrimonio
Metrics:
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Data in Brief | Data in Brief | IRIS Cnr | IRIS Cnr | CNR IRIS
2023
Other
Restricted
THE D.3.2.1 - AA@THE User needs, technical requirements and specifications
Pratali L, Campana M G, Delmastro F, Di Martino F, Pescosolido L, Barsocchi P, Broccia G, Ciancia V, Gennaro C, Girolami M, Lagani G, La Rosa D, Latella D, Magrini M, Manca M, Massink M, Mattioli A, Moroni D, Palumbo F, Paradisi P, Paternò F, Santoro C, Sebastiani L, Vairo C
Deliverable D3.2.1 del progetto PNRR Ecosistemi ed innovazione - THE
Pratali L, Campana M G, Delmastro F, Di Martino F, Pescosolido L, Barsocchi P, Broccia G, Ciancia V, Gennaro C, Girolami M, Lagani G, La Rosa D, Latella D, Magrini M, Manca M, Massink M, Mattioli A, Moroni D, Palumbo F, Paradisi P, Paternò F, Santoro C, Sebastiani L, Vairo C
Deliverable D3.2.1 del progetto PNRR Ecosistemi ed innovazione - THE
2023
Conference article
Open Access
IoT smart shoe solution for neuromuscular disease monitoring
La Rosa D, Palumbo F, Ronca A, Sansone F, Tesconi M, Tonacci A, Conte R
Recent advances in sensing, processing, and learning of physiological parameters, make the development of non-invasive health monitoring systems increasingly effective, especially in those situations that need particular attention to the usability of devices and software solutions due to the frailty of the target population. In this context, we developed a sensorized shoe that detects significant features in subjects' gait and monitors variations related to an intervention protocol in people affected by Neuromuscular Disorders (NMDs). This paper outlines the challenges in the field and summarizes the approach used to overcome the technological barriers related to connectivity, deployment, and usability that are typical in a medical setting. The proposed solution adopts the new paradigm offered by Web Bluetooth based on Bluetooth WebSocket. We show the architectural and deployment choices and how this solution can be easily adapted to different devices and scenarios.Source: LECTURE NOTES OF THE INSTITUTE FOR COMPUTER SCIENCES, SOCIAL INFORMATICS AND TELECOMMUNICATIONS ENGINEERING (INTERNET), pp. 104-115. Thessaloniki, Greece, 12-14/12/2022
DOI: 10.1007/978-3-031-34586-9_8
Metrics:
La Rosa D, Palumbo F, Ronca A, Sansone F, Tesconi M, Tonacci A, Conte R
Recent advances in sensing, processing, and learning of physiological parameters, make the development of non-invasive health monitoring systems increasingly effective, especially in those situations that need particular attention to the usability of devices and software solutions due to the frailty of the target population. In this context, we developed a sensorized shoe that detects significant features in subjects' gait and monitors variations related to an intervention protocol in people affected by Neuromuscular Disorders (NMDs). This paper outlines the challenges in the field and summarizes the approach used to overcome the technological barriers related to connectivity, deployment, and usability that are typical in a medical setting. The proposed solution adopts the new paradigm offered by Web Bluetooth based on Bluetooth WebSocket. We show the architectural and deployment choices and how this solution can be easily adapted to different devices and scenarios.Source: LECTURE NOTES OF THE INSTITUTE FOR COMPUTER SCIENCES, SOCIAL INFORMATICS AND TELECOMMUNICATIONS ENGINEERING (INTERNET), pp. 104-115. Thessaloniki, Greece, 12-14/12/2022
DOI: 10.1007/978-3-031-34586-9_8
Metrics:
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CNR IRIS | link.springer.com | ISTI Repository | CNR IRIS | CNR IRIS
2023
Journal article
Open Access
Enerduino-pro: smart meter led probe using Arduino
Potortì F., La Rosa D., Palumbo F.
Non-intrusive load monitoring of domestic appliances has received steady interest in the last twenty years, first because of interest from energy companies interested in usage statistics for power balancing and, more recently, in order to assist users in tuning their habits for reduced power consumption. This has increased the need for accurate and economic methods of power measurement that can be efficiently implemented on cheap and easy-to-install platforms. To this end, we present a cheap and efficient device based on Arduino to monitor the usage of domestic appliances in real-time: Enerduino-pro. The design uses low-cost easy-to-assemble open-source electronic components and consists of four main parts: an Arduino UNO microcontroller, one photoresistor to measure instantaneous power absorption plus one optional additional one to measure reactive power, a WiFi shield, and an LED (for debugging purposes only). We describe the device, complete with open software and hardware specifications, and different use cases with proof-of-concept solutions.Source: HARDWAREX, vol. 15
DOI: 10.1016/j.ohx.2023.e00461
Metrics:
Potortì F., La Rosa D., Palumbo F.
Non-intrusive load monitoring of domestic appliances has received steady interest in the last twenty years, first because of interest from energy companies interested in usage statistics for power balancing and, more recently, in order to assist users in tuning their habits for reduced power consumption. This has increased the need for accurate and economic methods of power measurement that can be efficiently implemented on cheap and easy-to-install platforms. To this end, we present a cheap and efficient device based on Arduino to monitor the usage of domestic appliances in real-time: Enerduino-pro. The design uses low-cost easy-to-assemble open-source electronic components and consists of four main parts: an Arduino UNO microcontroller, one photoresistor to measure instantaneous power absorption plus one optional additional one to measure reactive power, a WiFi shield, and an LED (for debugging purposes only). We describe the device, complete with open software and hardware specifications, and different use cases with proof-of-concept solutions.Source: HARDWAREX, vol. 15
DOI: 10.1016/j.ohx.2023.e00461
Metrics:
See at:
CNR IRIS | ISTI Repository | www.sciencedirect.com | CNR IRIS
2023
Conference article
Open Access
On the analysis of body orientation for indoor positioning with BLE 5.1 direction finding
Mavilia F, Barsocchi P, Furfari F, La Rosa D, Girolami M
The last decade showed a clear technological trend toward the adoption of heterogeneous source of information, combined with data-fusion strategies to increase the performance of indoor localization systems. In this respect, the adoption of short-range network protocols such as WiFi and Bluetooth represent a common approach. We investigate, in this work, the use of Bluetooth 5.1 Direction Finding specification to test an indoor localization system solely based on the estimated Angle of Arrival (AoA) between an anchor and a receiver. We first detail our experimental data collection campaign and the adopted hardware. Then, we study not only the accuracy of the estimated angles on two reference planes but also the localization error introduced with the proposed algorithm by varying the body orientation of the target user, namely North, South, West, Est. Experimental results in a real-world indoor environment show an average localization error of 2.08m with only 1 anchor node and 5° of AoA' error for all 28 monitored locations. We also identify regions in which the AoA estimation rapidly decreases, giving rise to the possibility of identifying the boundaries of the adopted technology.DOI: 10.1109/icc45041.2023.10279029
Metrics:
Mavilia F, Barsocchi P, Furfari F, La Rosa D, Girolami M
The last decade showed a clear technological trend toward the adoption of heterogeneous source of information, combined with data-fusion strategies to increase the performance of indoor localization systems. In this respect, the adoption of short-range network protocols such as WiFi and Bluetooth represent a common approach. We investigate, in this work, the use of Bluetooth 5.1 Direction Finding specification to test an indoor localization system solely based on the estimated Angle of Arrival (AoA) between an anchor and a receiver. We first detail our experimental data collection campaign and the adopted hardware. Then, we study not only the accuracy of the estimated angles on two reference planes but also the localization error introduced with the proposed algorithm by varying the body orientation of the target user, namely North, South, West, Est. Experimental results in a real-world indoor environment show an average localization error of 2.08m with only 1 anchor node and 5° of AoA' error for all 28 monitored locations. We also identify regions in which the AoA estimation rapidly decreases, giving rise to the possibility of identifying the boundaries of the adopted technology.DOI: 10.1109/icc45041.2023.10279029
Metrics:
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CNR IRIS | ieeexplore.ieee.org | ISTI Repository | CNR IRIS | CNR IRIS
2023
Journal article
Open Access
A CrowdSensing-based approach for proximity detection in indoor museums with bluetooth tags
Girolami M, La Rosa D, Barsocchi P
In this work, we investigate the performance of a proximity detection system for visitors in an indoor museum exploiting data collected from the crowd. More specifically, we propose a CrowdSensing-based technique for proximity detection. Users' smartphones can collect and upload RSS (Received Signal Strength) values of nearby Bluetooth tags to a backend server, together with some context-information. In turn, the collected data are elaborated with the goal of calibrating two proximity detection algorithms: a range-based and a learning-based algorithm. We embed the algorithms with R-app, a visiting museum application tested in the Monumental Cemetery's museum located in Piazza dei Miracoli, Pisa (IT). We detail in this work an experimental campaign to measure the performance improvements of the CrowdSensing approach with respect to state-of-the-art algorithms widely adopted in the field of proximity detection. Experimental results show a clear improvement of the performance when data from the crowd are exploited with the proposed architecture.Source: AD HOC NETWORKS, vol. 154
DOI: 10.1016/j.adhoc.2023.103367
Metrics:
Girolami M, La Rosa D, Barsocchi P
In this work, we investigate the performance of a proximity detection system for visitors in an indoor museum exploiting data collected from the crowd. More specifically, we propose a CrowdSensing-based technique for proximity detection. Users' smartphones can collect and upload RSS (Received Signal Strength) values of nearby Bluetooth tags to a backend server, together with some context-information. In turn, the collected data are elaborated with the goal of calibrating two proximity detection algorithms: a range-based and a learning-based algorithm. We embed the algorithms with R-app, a visiting museum application tested in the Monumental Cemetery's museum located in Piazza dei Miracoli, Pisa (IT). We detail in this work an experimental campaign to measure the performance improvements of the CrowdSensing approach with respect to state-of-the-art algorithms widely adopted in the field of proximity detection. Experimental results show a clear improvement of the performance when data from the crowd are exploited with the proposed architecture.Source: AD HOC NETWORKS, vol. 154
DOI: 10.1016/j.adhoc.2023.103367
Metrics:
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Ad Hoc Networks | CNR IRIS | ISTI Repository | ISTI Repository | www.sciencedirect.com | CNR IRIS | CNR IRIS
2023
Other
Restricted
ChAALenge D6.3 - Integrazione in laboratorio e analisi delle prestazioni
Bacco F. M., Baronti P., Barsocchi P., Belli D., Crivello A., Furfari F., Girolami M., La Rosa D., Mavilia F., Miori V., Palumbo F., Potortì F., Russo D.
Report di laboratorio di analisi dei risultati dell’integrazione e indagine prestazionale sul framework integrato contenente: (i) Risultati attinenti alla validità dei dati acquisiti dal framework, al fine del loro efficiente utilizzo da parte degli algoritmi sviluppati; (ii) Risultati riguardanti la correttezza, completezza e affidabilità dell’esito della sperimentazione sia in laboratorio sia sul campo e relativi alla valutazione prestazionale del software di sistema.Project(s): ChAALenge
Bacco F. M., Baronti P., Barsocchi P., Belli D., Crivello A., Furfari F., Girolami M., La Rosa D., Mavilia F., Miori V., Palumbo F., Potortì F., Russo D.
Report di laboratorio di analisi dei risultati dell’integrazione e indagine prestazionale sul framework integrato contenente: (i) Risultati attinenti alla validità dei dati acquisiti dal framework, al fine del loro efficiente utilizzo da parte degli algoritmi sviluppati; (ii) Risultati riguardanti la correttezza, completezza e affidabilità dell’esito della sperimentazione sia in laboratorio sia sul campo e relativi alla valutazione prestazionale del software di sistema.Project(s): ChAALenge
2023
Other
Open Access
D3.2.1: AA@THE User needs, technical requirements and specifications
Lorenza Pratali, Franca Delmastro, Mattia Campana, Flavio Di Martino, Loreto Pescosolido, Paolo Barsocchi, Giovanna Broccia, Vincenzo Ciancia, Claudio Gennaro, Michele Girolami, Gabriele Lagani, Diego Latella, Massimo Magrini, Marco Manca, Mieke Massink, Andrea Mattioli, Davide Moroni, Filippo Palumbo, Paolo Paradisi, Fabio Paternò, Laura Sebastiani, Claudio Vairo, Carmelina Santoro, Davide La Rosa
The objective of this deliverable is to compile a comprehensive report that describes the user needs, requirements, and technical specifications necessary to successfully implement the pilot study. To achieve this, it is crucial to establish contacts with specific associations and medical experts, which, collaboratively, will help to establish exclusion and inclusion criteria for the target population of healthy adults. Furthermore, another related objective is to define the different categories of users that will interact with the system and their specific needs. This holistic approach will ensure that the system is designed and developed to satisfy the diverse needs of the users and be aligned with the goals of the project. To achieve the milestone M3.2.1, we made significant progresses in the definition of the pilot study for the AA@THE subproject. One of our key achievements is the successful description of users’ needs, requirements, and technical specifications necessary for the study. We worked closely with both a specialized association of personal trainers for Adapted Physical Activity (APA) for older adults, already active in the area of Pisa, and the medical partner who played a crucial role in providing valuable insights and expertise to establish exclusion and inclusion criteria for the target population of healthy adults. In this milestone, we also defined the activities and services that we intend to offer. Specifically, we plan to provide technological systems aimed at monitoring physical and cognitive training processes, as well as stability evaluations, by instrumenting a gym dedicated to active and healthy ageing, which is located within the CNR research area in Pisa. Additionally, we will conduct sleep, nutrition, and sedentary assessments at the volunteers' homes. Furthermore, we successfully defined the different user categories involved in the study. To facilitate the recruitment process and people engagement, on January 17th 2023, we organized an open day in collaboration with the gym association where we presented the overall objectives of the project and we collected feedbacks from a group of healthy adults over 65, already involved in APA training. This allowed us to gain a comprehensive understanding of the users' specific needs in terms of system interactions, thus establishing the system requirements and technical specifications of the AA@THE ecosystem. In parallel, a specific action on “Automatic Support of Medical Image Analysis” has been initiated by members of the “Formal Methods and Tools” group at CNR-ISTI. Such an action aims at leveraging Formal Methods in Computer Science, Logic and Model Checking to augment state-of-the-art machine learning techniques for automatic medical image analysis, enabling end-users to make specific assumptions on the level of accountability and affordability of the system. The methodology is based on a strict intertwining between theory and experimentation, with the development of new theoretical foundations for model reduction and efficient model checking, and experimentation and finalization of a graphical user interface that is being evaluated from the points of view of usability and of cognitive load. Moreover, the design and implementation of a suitable GUI able to support the analysis of medical images has been conducted and tested with small groups of people derived from the hospital in Lucca. The proposed GUI prototype has been evaluated from a cognitive point of view in order to allow easy employment with little training, for general practitioners and caregivers who may lack the technical skills required to use fully-fledged medical imaging programs.Project(s): Tuscany Health Ecosystem
Lorenza Pratali, Franca Delmastro, Mattia Campana, Flavio Di Martino, Loreto Pescosolido, Paolo Barsocchi, Giovanna Broccia, Vincenzo Ciancia, Claudio Gennaro, Michele Girolami, Gabriele Lagani, Diego Latella, Massimo Magrini, Marco Manca, Mieke Massink, Andrea Mattioli, Davide Moroni, Filippo Palumbo, Paolo Paradisi, Fabio Paternò, Laura Sebastiani, Claudio Vairo, Carmelina Santoro, Davide La Rosa
The objective of this deliverable is to compile a comprehensive report that describes the user needs, requirements, and technical specifications necessary to successfully implement the pilot study. To achieve this, it is crucial to establish contacts with specific associations and medical experts, which, collaboratively, will help to establish exclusion and inclusion criteria for the target population of healthy adults. Furthermore, another related objective is to define the different categories of users that will interact with the system and their specific needs. This holistic approach will ensure that the system is designed and developed to satisfy the diverse needs of the users and be aligned with the goals of the project. To achieve the milestone M3.2.1, we made significant progresses in the definition of the pilot study for the AA@THE subproject. One of our key achievements is the successful description of users’ needs, requirements, and technical specifications necessary for the study. We worked closely with both a specialized association of personal trainers for Adapted Physical Activity (APA) for older adults, already active in the area of Pisa, and the medical partner who played a crucial role in providing valuable insights and expertise to establish exclusion and inclusion criteria for the target population of healthy adults. In this milestone, we also defined the activities and services that we intend to offer. Specifically, we plan to provide technological systems aimed at monitoring physical and cognitive training processes, as well as stability evaluations, by instrumenting a gym dedicated to active and healthy ageing, which is located within the CNR research area in Pisa. Additionally, we will conduct sleep, nutrition, and sedentary assessments at the volunteers' homes. Furthermore, we successfully defined the different user categories involved in the study. To facilitate the recruitment process and people engagement, on January 17th 2023, we organized an open day in collaboration with the gym association where we presented the overall objectives of the project and we collected feedbacks from a group of healthy adults over 65, already involved in APA training. This allowed us to gain a comprehensive understanding of the users' specific needs in terms of system interactions, thus establishing the system requirements and technical specifications of the AA@THE ecosystem. In parallel, a specific action on “Automatic Support of Medical Image Analysis” has been initiated by members of the “Formal Methods and Tools” group at CNR-ISTI. Such an action aims at leveraging Formal Methods in Computer Science, Logic and Model Checking to augment state-of-the-art machine learning techniques for automatic medical image analysis, enabling end-users to make specific assumptions on the level of accountability and affordability of the system. The methodology is based on a strict intertwining between theory and experimentation, with the development of new theoretical foundations for model reduction and efficient model checking, and experimentation and finalization of a graphical user interface that is being evaluated from the points of view of usability and of cognitive load. Moreover, the design and implementation of a suitable GUI able to support the analysis of medical images has been conducted and tested with small groups of people derived from the hospital in Lucca. The proposed GUI prototype has been evaluated from a cognitive point of view in order to allow easy employment with little training, for general practitioners and caregivers who may lack the technical skills required to use fully-fledged medical imaging programs.Project(s): Tuscany Health Ecosystem