Technological monitoring of motor parameters to assess multidimensional frailty of older people in the PRO-HOME project
Abstract An interconnected system employing Kinect Azure and Fitbit Sense for continuous and non-intrusive data collection was used in the PRO-HOME protected discharge program, aiming at monitoring functional and clinical parameters in hospitalized older patients at different risks of frailty. The p...
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Nature Portfolio
2024-12-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-024-80061-6 |
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| author | Emanuele Seminerio Wanda Morganti Marina Barbagelata Sanket Rajeev Sabharwal Simone Ghisio Camilla Prete Barbara Senesi Simone Dini Romina Custureri Simonetta Galliani Simona Morelli Gianluca Puleo Carlo Berutti-Bergotto Antonio Camurri Alberto Pilotto PRO-HOME Project Investigators Group |
| author_facet | Emanuele Seminerio Wanda Morganti Marina Barbagelata Sanket Rajeev Sabharwal Simone Ghisio Camilla Prete Barbara Senesi Simone Dini Romina Custureri Simonetta Galliani Simona Morelli Gianluca Puleo Carlo Berutti-Bergotto Antonio Camurri Alberto Pilotto PRO-HOME Project Investigators Group |
| author_sort | Emanuele Seminerio |
| collection | DOAJ |
| description | Abstract An interconnected system employing Kinect Azure and Fitbit Sense for continuous and non-intrusive data collection was used in the PRO-HOME protected discharge program, aiming at monitoring functional and clinical parameters in hospitalized older patients at different risks of frailty. The present study shows the findings on 30 older patients included in the PRO-HOME project. The Fitbit Sense recorded the mean daily and hourly number of steps, mean daily walked distance, and time spent inactive. Moreover, Kinect infrared camera captured gait speed and daily mean latero-lateral (body sway) and antero-posterior oscillations (lean-in). Patients underwent a standard Comprehensive Geriatric Assessment (CGA) to compute the Multidimensional Prognostic Index (MPI), including basic and instrumental activities of daily living (ADL, IADL), cognition (Short Portable Mental Status Questionnaire, SPMSQ) and nutrition, risk of pressure sores (Exton-Smith Scale, ESS), comorbidity, number of drugs and cohabitation status. Significant correlations between the mean hourly number of steps and MPI (p = 0.022), IADL (p = 0.013), SPMSQ (p = 0.006), ESS (p = 0.009), and both mean and maximum automated gait speed (p = 0.046 and p = 0.048) were found. Automated gait speed was also correlated with mean walked distance per day (p = 0.007) and lean-in (p = 0.047). Domotic technological monitoring through Fitbit Sense and Kinect Azure provides information on multidimensional frailty, including mobility and cognitive and functional status, in older people. |
| format | Article |
| id | doaj-art-b25a6f779295451780ebb27b08e273a6 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-b25a6f779295451780ebb27b08e273a62024-12-08T12:31:28ZengNature PortfolioScientific Reports2045-23222024-12-0114111010.1038/s41598-024-80061-6Technological monitoring of motor parameters to assess multidimensional frailty of older people in the PRO-HOME projectEmanuele Seminerio0Wanda Morganti1Marina Barbagelata2Sanket Rajeev Sabharwal3Simone Ghisio4Camilla Prete5Barbara Senesi6Simone Dini7Romina Custureri8Simonetta Galliani9Simona Morelli10Gianluca Puleo11Carlo Berutti-Bergotto12Antonio Camurri13Alberto Pilotto14PRO-HOME Project Investigators GroupGeriatrics Unit, Department of Geriatric Care, Neurology and Rehabilitation, Galliera HospitalGeriatrics Unit, Department of Geriatric Care, Neurology and Rehabilitation, Galliera HospitalGeriatrics Unit, Department of Geriatric Care, Neurology and Rehabilitation, Galliera HospitalDepartment of Informatics, Bioengineering, Robotics and System Engineering, Casa Paganini-InfoMus Research Center, University of GenovaDepartment of Informatics, Bioengineering, Robotics and System Engineering, Casa Paganini-InfoMus Research Center, University of GenovaGeriatrics Unit, Department of Geriatric Care, Neurology and Rehabilitation, Galliera HospitalGeriatrics Unit, Department of Geriatric Care, Neurology and Rehabilitation, Galliera HospitalGeriatrics Unit, Department of Geriatric Care, Neurology and Rehabilitation, Galliera HospitalGeriatrics Unit, Department of Geriatric Care, Neurology and Rehabilitation, Galliera HospitalGeriatrics Unit, Department of Geriatric Care, Neurology and Rehabilitation, Galliera HospitalGeriatrics Unit, Department of Geriatric Care, Neurology and Rehabilitation, Galliera HospitalGeriatrics Unit, Department of Geriatric Care, Neurology and Rehabilitation, Galliera HospitalInformatic and Technology Unit, Galliera HospitalDepartment of Informatics, Bioengineering, Robotics and System Engineering, Casa Paganini-InfoMus Research Center, University of GenovaGeriatrics Unit, Department of Geriatric Care, Neurology and Rehabilitation, Galliera HospitalAbstract An interconnected system employing Kinect Azure and Fitbit Sense for continuous and non-intrusive data collection was used in the PRO-HOME protected discharge program, aiming at monitoring functional and clinical parameters in hospitalized older patients at different risks of frailty. The present study shows the findings on 30 older patients included in the PRO-HOME project. The Fitbit Sense recorded the mean daily and hourly number of steps, mean daily walked distance, and time spent inactive. Moreover, Kinect infrared camera captured gait speed and daily mean latero-lateral (body sway) and antero-posterior oscillations (lean-in). Patients underwent a standard Comprehensive Geriatric Assessment (CGA) to compute the Multidimensional Prognostic Index (MPI), including basic and instrumental activities of daily living (ADL, IADL), cognition (Short Portable Mental Status Questionnaire, SPMSQ) and nutrition, risk of pressure sores (Exton-Smith Scale, ESS), comorbidity, number of drugs and cohabitation status. Significant correlations between the mean hourly number of steps and MPI (p = 0.022), IADL (p = 0.013), SPMSQ (p = 0.006), ESS (p = 0.009), and both mean and maximum automated gait speed (p = 0.046 and p = 0.048) were found. Automated gait speed was also correlated with mean walked distance per day (p = 0.007) and lean-in (p = 0.047). Domotic technological monitoring through Fitbit Sense and Kinect Azure provides information on multidimensional frailty, including mobility and cognitive and functional status, in older people.https://doi.org/10.1038/s41598-024-80061-6Multidimensional frailtyComprehensive geriatric assessmentOlder peopleTechnological monitoring |
| spellingShingle | Emanuele Seminerio Wanda Morganti Marina Barbagelata Sanket Rajeev Sabharwal Simone Ghisio Camilla Prete Barbara Senesi Simone Dini Romina Custureri Simonetta Galliani Simona Morelli Gianluca Puleo Carlo Berutti-Bergotto Antonio Camurri Alberto Pilotto PRO-HOME Project Investigators Group Technological monitoring of motor parameters to assess multidimensional frailty of older people in the PRO-HOME project Scientific Reports Multidimensional frailty Comprehensive geriatric assessment Older people Technological monitoring |
| title | Technological monitoring of motor parameters to assess multidimensional frailty of older people in the PRO-HOME project |
| title_full | Technological monitoring of motor parameters to assess multidimensional frailty of older people in the PRO-HOME project |
| title_fullStr | Technological monitoring of motor parameters to assess multidimensional frailty of older people in the PRO-HOME project |
| title_full_unstemmed | Technological monitoring of motor parameters to assess multidimensional frailty of older people in the PRO-HOME project |
| title_short | Technological monitoring of motor parameters to assess multidimensional frailty of older people in the PRO-HOME project |
| title_sort | technological monitoring of motor parameters to assess multidimensional frailty of older people in the pro home project |
| topic | Multidimensional frailty Comprehensive geriatric assessment Older people Technological monitoring |
| url | https://doi.org/10.1038/s41598-024-80061-6 |
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