Selecting and utilising smart wearables
7. Resources
Chow, H. W., & Yang, C. C. (2020). Accuracy of optical heart rate sensing technology in wearable fitness trackers for young and older adults: validation and comparison study. JMIR mHealth and uHealth, 8(4), e14707. https://doi.org/10.2196/14707
Ehn, M., Eriksson, L. C., Åkerberg, N., & Johansson, A. C. (2018). Activity monitors as support for older persons’ physical activity in daily life: qualitative study of the users’ experiences. JMIR mHealth and uHealth, 6(2), e8345. https://doi.org/10.2196/mhealth.8345
Frey-Law, L. A., Merkle, S. L., Dailey, D., & Sluka, K. A. (2024). Nonlinear modification to Hildebrand equation for accelerometry assessment of physical activity: improved accuracy for low activity levels. Exploration of Musculoskeletal Diseases, 2(5), 408-422. https://doi.org/10.37349/emd.2024.00066
Fries, J.F., & Crapo, L.M. (1981). Vitality and aging. San Francisco: Freeman.
Gao, W., Du, K., Luo, Y., Shi, W., & Shi, Y. (2024). EasyAsk: An In-App Contextual Tutorial Search Assistant for Older Adults. Interactive, Mobile, Wearable and Ubiquitous Technologies, 8, 3. https://doi.org/10.1145/3678516
Greengard, S., Virtual Reality. 2019: MIT Press.
Jacobson, B.H., Smith, D., Fronterhouse, J., Kline, C., & Boolani, A. (2012). Assessment of the benefit of powered exercises for muscular endurance and functional capacity in elderly participants, Journal of Physical Activity and Health, 9, 1030-1035. https://doi.org/10.1123/jpah.9.7.1030
Kaplan, A.D., et al., The Effects of Virtual Reality, Augmented Reality, and Mixed Reality as Training Enhancement Methods: A Meta-Analysis. Human Factors, 2021. 63(4): p. 706-726.
Kanning, M. & Schlicht, W. (2010). Be active and become happy: an ecological momentary assessment of physical activity and mood. Journal of Sport and Exercise Psychology, 32, 253-261. https://doi.org/10.1123/jsep.32.2.253
Kimura, N., Masuda, T., Ataka, T., & Matsubara, E. (2024). Relationship between measured conversation time and social behavior in community-dwelling older adults. Frontiers in Neurology, 15 https://doi.org/10.3389/fneur.2024.1479296
Kononova, A., Li, L., Kamp, K., Bowen, M., Rikard, R. V., Cotten, S., & Peng, W. (2019). The use of wearable activity trackers among older adults: focus group study of tracker perceptions, motivators, and barriers in the maintenance stage of behavior change. JMIR mHealth and uHealth, 7(4), e9832. https://doi.org/10.2196/mhealth.9832
Lee, J. Y., & Lee, S. Y. (2024). Development of AI-based predictive algorithm for early diagnosis of high-risk dementia groups among the elderly: Utilizing health lifelog data. Healthcare, 12(18), 1872. https://doi.org/10.3390/healthcare12181872
Li, J., Ma, Q., Chan, A. H., & Man, S. (2019). Health monitoring through wearable technologies for older adults: Smart wearables acceptance model. Applied Ergonomics, 75, 162-169. https://doi.org/10.1016/j.apergo.2018.10.006
Lin, Charles & Lee, Chaiwoo & Lally, Dennis & Coughlin, Joseph. (2018). Impact of Virtual Reality (VR) Experience on Older Adults’ Well-Being. 10.1007/978-3-319-92037-5_8.
Liang, P. (2024). Development of Next Generation Assistive Wearable Device. Unpublished thesis dissertation, University of Technology Sydney.
Mandal, S. Brief Introduction of Virtual Reality & its Challenges. 2013.
Martinato, M., Lorenzoni, G., Zanchi, T., et al. (2021). Usability and accuracy of a smartwatch for the assessment of physical activity in the elderly population: Observational study. JMIR mHealth and uHealth, 9(5), e20966. https://doi.org/10.2196/20966
Moore, K., O'Shea, E., Kenny, L., Barton, J., Tedesco, S., Sica, M., ... & Timmons, S. (2021). Older adults’ experiences with using wearable devices: qualitative systematic review and meta-synthesis. JMIR mHealth and uHealth, 9(6), e23832. https://doi.org/10.2196/23832
Nurmi, J., Knittle, K., Ginchev, T., Khattak, F., Helf, C., Zwickl, P., ... & Haukkala, A. (2020). Engaging users in the behavior change process with digitalized motivational interviewing and gamification: Development and feasibility testing of the PRECIOUS app. JMIR mHealth and uHealth, 8(1), e12884. https://doi.org/10.2196/12884
Olmedo-Aguirre, J. O., Reyes-Campos, J., Alor-Hernandez, G., Machorro-Cano, I., Rodriguez-Mazahua, L., & Sanchez-Cervantes, J. L. (2022). Remote healthcare for elderly people using wearables: A review. Biosensors, 12(2), 73. https://doi.org/10.3390/bios12020073
Paraschiakos, S., Cachucho, R., Moed, M. et al. Activity recognition using wearable sensors for tracking the elderly. User Modeling and User-Adapted Interaction, 30, 567–605. https://doi.org/10.1007/s11257-020-09268-2
Peng, W., Li, L., Kononova, A., Cotten, S., Kamp, K., & Bowen, M. (2021). Habit formation in wearable activity tracker use among older adults: qualitative study. JMIR mHealth and uHealth, 9(1), e22488. https://doi.org/10.2196/22488
Pichandi, K. V., Senthil, P., Prabakar, D., & Uma, S. (2025). Artificial internet of medical things for wearable body sensor data analysis. Expert Systems with Applications, 260, 125338. https://doi.org/10.1016/j.eswa.2024.125338
Ramalho A, Duarte-Mendes P, Paulo R, Serrano J, Petrica J. Crossing the digital frontier: are older adults ready for virtual reality workouts? Front Public Health. 2024 Feb 8;12:1324004. doi: 10.3389/fpubh.2024.1324004. PMID: 38389949; PMCID: PMC10881650.
Rose, D. J. & Skelton, D. A. (2019). The field of Gerokinesiology. In D. J. Rose (Ed.), Physical activity instruction of older adults (2nd ed.), pp. 1-15. Champaign IL: Human Kinetics.
Saleh Kalantari, Tong Bill Xu, Armin Mostafavi, Benjamin Kim, Andrew Dilanchian, Angella Lee, Walter R Boot, Sara J Czaja, Using Immersive Virtual Reality to Enhance Social Interaction Among Older Adults: A Cross-Site Investigation, Innovation in Aging, Volume 7, Issue 4, 2023, igad031, https://doi.org/10.1093/geroni/igad031
Teixeira, E., Fonseca, H., Diniz-Sousa, F., Veras, L., et al. (2021). Wearable devices for physical activity and healthcare monitoring in elderly people: A critical review. Geriatrics, 6, 38. https://doi.org/10.3390/geriatrics6020038
The Role of Virtual Reality in Promoting Healthy Aging and Active Lifestyles | FXMedia: Solutions for Metaverse. (2024). Fxmweb.com. https://www.fxmweb.com/insights/the-role-of-virtual-reality-in-promoting-healthy-aging-and-active-lifestyles.html
van Gameren, M., Voorn, P. B., Bossen, D., et al. (2024). The Short Physical Performance Battery does not correlate with daily life gait quality and quantity in community-dwelling older adults with an increased fall risk. Gait & Posture, 114, 78-83. https://doi.org/10.1016/j.gaitpost.2024.09.005
Vargemidis, D., Gerling, K., Spiel, K., Abeele, V. V., & Geurts, L. (2020). Wearable physical activity tracking systems for older adults—a systematic review. ACM Transactions on Computing for Healthcare, 1(4), 1-37. https://doi.org/10.1145/3402523
Wall, C., Young, F., & McMeekin, P. (2024). CuePD: An IoT Approach for Enhancing Gait Rehabilitation in Older Adults through Personalized Music Cueing. IEEE Sensors Journal, 8, 1-4. https://doi.org/10.1109/LSENS.2024.3456855
Wang, L.-T. (2023). Effectiveness of Virtual Reality Exercise for Functional Fitness in Community-Dwelling Older Adults: A 12-Week Follow-Up Study. Sage Open, 13(4). https://doi.org/10.1177/21582440231218515
Wardi, G., Nemati, S., & Nagarajan, V. (2024). 161 use of wearable data to predict emergency department revisits. Annals of Emergency Medicine. 84(4), S76. https://doi.org/10.1016/j.annemergmed.2024.08.167
Yan, J.H. & Zhou, C.L. (2009). Effects of motor practice on cognitive disorders in older adults. European Group for Research into Elderly and Physical Activity, 6, 67-74. https://doi.org/10.1007/s11556-009-0049-6
Yan, Q. S., & Guo, Q. (2024). Enhancement or Suppression? Differential Association of Digital Literacy with Subjective Health of Older Adults. Frontiers in Public Health, 12 https://doi.og/10.3389/fpubh.2024.1395162
Yang, Q., Mamun, A. A., Wu, M., & Naznen, F. (2024). Strengthening health monitoring: Intention and adoption of IoT-enabled wearable healthcare devices. Digital Health, 10, https://doi.org/10.1177/2055207624127919
Chow, H. W., & Yang, C. C. (2020). Accuracy of optical heart rate sensing technology in wearable fitness trackers for young and older adults: validation and comparison study. JMIR mHealth and uHealth, 8(4), e14707. https://doi.org/10.2196/14707
Ehn, M., Eriksson, L. C., Åkerberg, N., & Johansson, A. C. (2018). Activity monitors as support for older persons’ physical activity in daily life: qualitative study of the users’ experiences. JMIR mHealth and uHealth, 6(2), e8345. https://doi.org/10.2196/mhealth.8345
Frey-Law, L. A., Merkle, S. L., Dailey, D., & Sluka, K. A. (2024). Nonlinear modification to Hildebrand equation for accelerometry assessment of physical activity: improved accuracy for low activity levels. Exploration of Musculoskeletal Diseases, 2(5), 408-422. https://doi.org/10.37349/emd.2024.00066
Fries, J.F., & Crapo, L.M. (1981). Vitality and aging. San Francisco: Freeman.
Gao, W., Du, K., Luo, Y., Shi, W., & Shi, Y. (2024). EasyAsk: An In-App Contextual Tutorial Search Assistant for Older Adults. Interactive, Mobile, Wearable and Ubiquitous Technologies, 8, 3. https://doi.org/10.1145/3678516
Greengard, S., Virtual Reality. 2019: MIT Press.
Jacobson, B.H., Smith, D., Fronterhouse, J., Kline, C., & Boolani, A. (2012). Assessment of the benefit of powered exercises for muscular endurance and functional capacity in elderly participants, Journal of Physical Activity and Health, 9, 1030-1035. https://doi.org/10.1123/jpah.9.7.1030
Kaplan, A.D., et al., The Effects of Virtual Reality, Augmented Reality, and Mixed Reality as Training Enhancement Methods: A Meta-Analysis. Human Factors, 2021. 63(4): p. 706-726.
Kanning, M. & Schlicht, W. (2010). Be active and become happy: an ecological momentary assessment of physical activity and mood. Journal of Sport and Exercise Psychology, 32, 253-261. https://doi.org/10.1123/jsep.32.2.253
Kimura, N., Masuda, T., Ataka, T., & Matsubara, E. (2024). Relationship between measured conversation time and social behavior in community-dwelling older adults. Frontiers in Neurology, 15 https://doi.org/10.3389/fneur.2024.1479296
Kononova, A., Li, L., Kamp, K., Bowen, M., Rikard, R. V., Cotten, S., & Peng, W. (2019). The use of wearable activity trackers among older adults: focus group study of tracker perceptions, motivators, and barriers in the maintenance stage of behavior change. JMIR mHealth and uHealth, 7(4), e9832. https://doi.org/10.2196/mhealth.9832
Lee, J. Y., & Lee, S. Y. (2024). Development of AI-based predictive algorithm for early diagnosis of high-risk dementia groups among the elderly: Utilizing health lifelog data. Healthcare, 12(18), 1872. https://doi.org/10.3390/healthcare12181872
Li, J., Ma, Q., Chan, A. H., & Man, S. (2019). Health monitoring through wearable technologies for older adults: Smart wearables acceptance model. Applied Ergonomics, 75, 162-169. https://doi.org/10.1016/j.apergo.2018.10.006
Lin, Charles & Lee, Chaiwoo & Lally, Dennis & Coughlin, Joseph. (2018). Impact of Virtual Reality (VR) Experience on Older Adults’ Well-Being. 10.1007/978-3-319-92037-5_8.
Liang, P. (2024). Development of Next Generation Assistive Wearable Device. Unpublished thesis dissertation, University of Technology Sydney.
Mandal, S. Brief Introduction of Virtual Reality & its Challenges. 2013.
Martinato, M., Lorenzoni, G., Zanchi, T., et al. (2021). Usability and accuracy of a smartwatch for the assessment of physical activity in the elderly population: Observational study. JMIR mHealth and uHealth, 9(5), e20966. https://doi.org/10.2196/20966
Moore, K., O'Shea, E., Kenny, L., Barton, J., Tedesco, S., Sica, M., ... & Timmons, S. (2021). Older adults’ experiences with using wearable devices: qualitative systematic review and meta-synthesis. JMIR mHealth and uHealth, 9(6), e23832. https://doi.org/10.2196/23832
Nurmi, J., Knittle, K., Ginchev, T., Khattak, F., Helf, C., Zwickl, P., ... & Haukkala, A. (2020). Engaging users in the behavior change process with digitalized motivational interviewing and gamification: Development and feasibility testing of the PRECIOUS app. JMIR mHealth and uHealth, 8(1), e12884. https://doi.org/10.2196/12884
Olmedo-Aguirre, J. O., Reyes-Campos, J., Alor-Hernandez, G., Machorro-Cano, I., Rodriguez-Mazahua, L., & Sanchez-Cervantes, J. L. (2022). Remote healthcare for elderly people using wearables: A review. Biosensors, 12(2), 73. https://doi.org/10.3390/bios12020073
Paraschiakos, S., Cachucho, R., Moed, M. et al. Activity recognition using wearable sensors for tracking the elderly. User Modeling and User-Adapted Interaction, 30, 567–605. https://doi.org/10.1007/s11257-020-09268-2
Peng, W., Li, L., Kononova, A., Cotten, S., Kamp, K., & Bowen, M. (2021). Habit formation in wearable activity tracker use among older adults: qualitative study. JMIR mHealth and uHealth, 9(1), e22488. https://doi.org/10.2196/22488
Pichandi, K. V., Senthil, P., Prabakar, D., & Uma, S. (2025). Artificial internet of medical things for wearable body sensor data analysis. Expert Systems with Applications, 260, 125338. https://doi.org/10.1016/j.eswa.2024.125338
Ramalho A, Duarte-Mendes P, Paulo R, Serrano J, Petrica J. Crossing the digital frontier: are older adults ready for virtual reality workouts? Front Public Health. 2024 Feb 8;12:1324004. doi: 10.3389/fpubh.2024.1324004. PMID: 38389949; PMCID: PMC10881650.
Rose, D. J. & Skelton, D. A. (2019). The field of Gerokinesiology. In D. J. Rose (Ed.), Physical activity instruction of older adults (2nd ed.), pp. 1-15. Champaign IL: Human Kinetics.
Saleh Kalantari, Tong Bill Xu, Armin Mostafavi, Benjamin Kim, Andrew Dilanchian, Angella Lee, Walter R Boot, Sara J Czaja, Using Immersive Virtual Reality to Enhance Social Interaction Among Older Adults: A Cross-Site Investigation, Innovation in Aging, Volume 7, Issue 4, 2023, igad031, https://doi.org/10.1093/geroni/igad031
Teixeira, E., Fonseca, H., Diniz-Sousa, F., Veras, L., et al. (2021). Wearable devices for physical activity and healthcare monitoring in elderly people: A critical review. Geriatrics, 6, 38. https://doi.org/10.3390/geriatrics6020038
The Role of Virtual Reality in Promoting Healthy Aging and Active Lifestyles | FXMedia: Solutions for Metaverse. (2024). Fxmweb.com. https://www.fxmweb.com/insights/the-role-of-virtual-reality-in-promoting-healthy-aging-and-active-lifestyles.html
van Gameren, M., Voorn, P. B., Bossen, D., et al. (2024). The Short Physical Performance Battery does not correlate with daily life gait quality and quantity in community-dwelling older adults with an increased fall risk. Gait & Posture, 114, 78-83. https://doi.org/10.1016/j.gaitpost.2024.09.005
Vargemidis, D., Gerling, K., Spiel, K., Abeele, V. V., & Geurts, L. (2020). Wearable physical activity tracking systems for older adults—a systematic review. ACM Transactions on Computing for Healthcare, 1(4), 1-37. https://doi.org/10.1145/3402523
Wall, C., Young, F., & McMeekin, P. (2024). CuePD: An IoT Approach for Enhancing Gait Rehabilitation in Older Adults through Personalized Music Cueing. IEEE Sensors Journal, 8, 1-4. https://doi.org/10.1109/LSENS.2024.3456855
Wang, L.-T. (2023). Effectiveness of Virtual Reality Exercise for Functional Fitness in Community-Dwelling Older Adults: A 12-Week Follow-Up Study. Sage Open, 13(4). https://doi.org/10.1177/21582440231218515
Wardi, G., Nemati, S., & Nagarajan, V. (2024). 161 use of wearable data to predict emergency department revisits. Annals of Emergency Medicine. 84(4), S76. https://doi.org/10.1016/j.annemergmed.2024.08.167
Yan, J.H. & Zhou, C.L. (2009). Effects of motor practice on cognitive disorders in older adults. European Group for Research into Elderly and Physical Activity, 6, 67-74. https://doi.org/10.1007/s11556-009-0049-6
Yan, Q. S., & Guo, Q. (2024). Enhancement or Suppression? Differential Association of Digital Literacy with Subjective Health of Older Adults. Frontiers in Public Health, 12 https://doi.og/10.3389/fpubh.2024.1395162
Yang, Q., Mamun, A. A., Wu, M., & Naznen, F. (2024). Strengthening health monitoring: Intention and adoption of IoT-enabled wearable healthcare devices. Digital Health, 10, https://doi.org/10.1177/2055207624127919
Chow, H. W., & Yang, C. C. (2020). Accuratezza della tecnologia di rilevamento ottico della frequenza cardiaca nei fitness tracker indossabili per adulti giovani e anziani: studio di convalida e confronto. JMIR mHealth and uHealth, 8(4), e14707. https://doi.org/10.2196/14707
Ehn, M., Eriksson, L. C., Åkerberg, N., & Johansson, A. C. (2018). Monitor di attività come supporto per l'attività fisica degli anziani nella vita quotidiana: studio qualitativo delle esperienze degli utenti. JMIR mHealth and uHealth, 6(2), e8345. https://doi.org/10.2196/mhealth.8345
Frey-Law, L. A., Merkle, S. L., Dailey, D. e Sluka, K. A. (2024). Modifica non lineare dell'equazione di Hildebrand per la valutazione accelerometrica dell'attività fisica: migliore accuratezza per i bassi livelli di attività. Esplorazione di malattie muscoloscheletriche Malattie Muscoloscheletriche, 2(5), 408-422. https://doi.org/10.37349/emd.2024.00066
Fries, J.F. e Crapo, L.M. (1981). Vitalità e invecchiamento. San Francisco: Freeman.
Gao, W., Du, K., Luo, Y., Shi, W., & Shi, Y. (2024). EasyAsk: An In-App Contextual Tutorial Search Assistant for Older Adults. Interactive, Mobile, Wearable and Ubiquitous Technologies, 8 , 3.https://doi.org/10.1145/3678516 Greengard, S., Realtà virtuale. 2019: MIT Press.
Jacobson, B.H., Smith, D., Fronterhouse, J., Kline, C., & Boolani, A. (2012). Valutazione del beneficio degli esercizi a motore per la resistenza muscolare e la capacità funzionale in partecipanti anziani, Journal of Physical Activity and Health, 9, 1030-1035. https://doi.org/10.1123/jpah.9.7.1030
Kaplan, A.D., et al., The Effects of Virtual Reality, Augmented Reality, and Mixed Reality as Training Enhancement Methods: Una meta-analisi. Fattori umani, 2021. 63(4): p. 706-726.
Kanning, M. & Schlicht, W. (2010). Essere attivi e diventare felici: una valutazione ecologica momentanea dell'attività fisica e dell'umore. Journal of Sport and Exercise Psychology, 32, 253-261. https://doi.org/10.1123/jsep.32.2.253
Kimura, N., Masuda, T., Ataka, T., & Matsubara, E. (2024). Relazione tra il tempo di conversazione misurato e il comportamento sociale in adulti anziani che vivono in comunità. Frontiers in Neurology,15 https://doi.org/10.3389/fneur.2024.1479296.
Kononova, A., Li, L., Kamp, K., Bowen, M., Rikard, R. V., Cotten, S., & Peng, W. (2019). L'uso di activity tracker indossabili tra gli anziani: studio di focus group sulle percezioni, i motivatori e le barriere del tracker nella fase di mantenimento del cambiamento comportamentale. JMIR mHealth and uHealth, 7(4), e9832. https://doi.org/10.2196/mhealth.9832
Lee, J. Y., & Lee, S. Y. (2024). Sviluppo di un algoritmo predittivo basato sull'intelligenza artificiale per la diagnosi precoce di gruppi di demenza ad alto rischio tra gli anziani: Utilizzando i dati del registro di vita della salute. Healthcare, 12(18), 1872. https://doi.org/10.3390/healthcare12181872
Li, J., Ma, Q., Chan, A. H., & Man, S. (2019). Monitoraggio della salute attraverso le tecnologie indossabili per gli adulti più anziani: Modello di accettazione degli indossabili intelligenti. Ergonomia applicata, 75, 162-169. https://doi.org/10.1016/j.apergo.2018.10.006
Lin, Charles & Lee, Chaiwoo & Lally, Dennis & Coughlin, Joseph. (2018). Impatto dell'esperienza di realtà virtuale (VR) sul benessere degli anziani. 10.1007/978-3-319-92037-5_8.
Liang, P. (2024). Sviluppo di un dispositivo indossabile di nuova generazione. Tesi di laurea non pubblicata, University of Technology Sydney.
Mandal, S. Breve introduzione alla realtà virtuale e alle sue sfide. 2013.
Martinato, M., Lorenzoni, G., Zanchi, T., et al. (2021). Usabilità e accuratezza di uno smartwatch per la valutazione dell'attività fisica nella popolazione anziana: Studio osservazionale. JMIR mHealth and uHealth, 9(5), e20966. https://doi.org/10.2196/20966
Moore, K., O'Shea, E., Kenny, L., Barton, J., Tedesco, S., Sica, M., ... e Timmons, S. (2021). Esperienze degli anziani nell'uso di dispositivi indossabili: revisione sistematica qualitativa e metasintesi. JMIR mHealth and uHealth, 9(6), e23832. https://doi.org/10.2196/23832
Nurmi, J., Knittle, K., Ginchev, T., Khattak, F., Helf, C., Zwickl, P., ... & Haukkala, A. (2020). Coinvolgere gli utenti nel processo di cambiamento del comportamento con il colloquio motivazionale digitalizzato e la gamification: Sviluppo e test di fattibilità dell'applicazione PRECIOUS. JMIR mHealth and uHealth, 8(1), e12884. https://doi.org/10.2196/12884
Olmedo-Aguirre, J. O., Reyes-Campos, J., Alor-Hernandez, G., Machorro-Cano, I., Rodriguez-Mazahua, L., & Sanchez- Cervantes, J. L. (2022). Assistenza sanitaria a distanza per gli anziani con i dispositivi indossabili: Una rassegna. Biosensors, 12(2), 73. https://doi.org/10.3390/bios12020073
Paraschiakos, S., Cachucho, R., Moed, M. et al. Riconoscimento dell'attività tramite sensori indossabili per il monitoraggio degli anziani. User Modeling and User-Adapted Interaction, 30, 567-605. https://doi.org/10.1007/s11257-020-09268-2
Peng, W., Li, L., Kononova, A., Cotten, S., Kamp, K., & Bowen, M. (2021). Formazione dell'abitudine all'uso di activity tracker indossabili tra gli adulti più anziani: studio qualitativo. JMIR mHealth and uHealth, 9(1), e22488. https://doi.org/10.2196/22488
Pichandi, K. V., Senthil, P., Prabakar, D. e Uma, S. (2025). Internet artificiale delle cose mediche per l'analisi dei dati dei sensori corporei indossabili. Sistemi esperti con applicazioni, 260, 125338. https://doi.org/10.1016/j.eswa.2024.125338
Ramalho A, Duarte-Mendes P, Paulo R, Serrano J, Petrica J. Attraversare la frontiera digitale: gli anziani sono pronti per gli allenamenti in realtà virtuale? Front Public Health. 2024 Feb 8;12:1324004. doi: 10.3389/fpubh.2024.1324004. PMID: 38389949; PMCID: PMC10881650.
Rose, D. J. & Skelton, D. A. (2019). Il campo della gerocinesiologia. In D. J. Rose (Ed.), Physical activity instruction of older adults (2nd ed.), pp. 1-15. Champaign IL: Human Kinetics.
Saleh Kalantari, Tong Bill Xu, Armin Mostafavi, Benjamin Kim, Andrew Dilanchian, Angella Lee, Walter R Boot, Sara J Czaja, Using Immersive Virtual Reality to Enhance Social Interaction Among Older Adults: A Cross-Site Investigation, Innovation in Aging, Volume 7, Issue 4, 2023, igad031, https://doi.org/10.1093/geroni/igad031
Teixeira, E., Fonseca, H., Diniz-Sousa, F., Veras, L., et al. (2021). Dispositivi indossabili per il monitoraggio dell'attività fisica e dell'assistenza sanitaria negli anziani: Una revisione critica. Geriatria, 6, 38. https://doi.org/10.3390/geriatrics6020038
Il ruolo della realtà virtuale nella promozione di un invecchiamento sano e di stili di vita attivi | FXMedia: Soluzioni per il Metaverso. (2024). Fxmweb.com. https://www.fxmweb.com/insights/the-role-of-virtual-reality-in- promoting- healthy-aging-and-active-lifestyles.html
van Gameren, M., Voorn, P. B., Bossen, D., et al. (2024). La Short Physical Performance Battery non è correlata con la qualità e la quantità dell'andatura nella vita quotidiana in adulti anziani che vivono in comunità e sono a rischio di caduta. Gait & Posture, 114, 78-83. https://doi.org/10.1016/j.gaitpost.2024.09.005
Vargemidis, D., Gerling, K., Spiel, K., Abeele, V. V., & Geurts, L. (2020). Sistemi indossabili di monitoraggio dell'attività fisica per adulti anziani: una revisione sistematica. ACM Transactions on Computing for Healthcare, 1(4), 1-37. https://doi.org/10.1145/3402523
Wall, C., Young, F. e McMeekin, P. (2024). CuePD: un approccio IoT per migliorare la riabilitazione dell'andatura negli anziani attraverso la musica personalizzata. IEEE Sensors Journal, 8, 1-4. https://doi.org/10.1109/LSENS.2024.3456855
Wang, L.-T. (2023). Efficacia dell'esercizio di realtà virtuale per il fitness funzionale negli anziani che vivono in comunità: A 12-Week Follow-Up Study. Sage Open, 13(4). https://doi.org/10.1177/21582440231218515
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Chow, H. W., & Yang, C. C. (2020). Accuracy of optical heart rate sensing technology in wearable fitness trackers for young and older adults: validation and comparison study. JMIR mHealth and uHealth, 8(4), e14707. https://doi.org/10.2196/14707
Ehn, M., Eriksson, L. C., Åkerberg, N., & Johansson, A. C. (2018). Activity monitors as support for older persons’ physical activity in daily life: qualitative study of the users’ experiences. JMIR mHealth and uHealth, 6(2), e8345. https://doi.org/10.2196/mhealth.8345
Frey-Law, L. A., Merkle, S. L., Dailey, D., & Sluka, K. A. (2024). Nonlinear modification to Hildebrand equation for accelerometry assessment of physical activity: improved accuracy for low activity levels. Exploration of Musculoskeletal Diseases, 2(5), 408-422. https://doi.org/10.37349/emd.2024.00066
Fries, J.F., & Crapo, L.M. (1981). Vitality and aging. San Francisco: Freeman.
Gao, W., Du, K., Luo, Y., Shi, W., & Shi, Y. (2024). EasyAsk: An In-App Contextual Tutorial Search Assistant for Older Adults. Interactive, Mobile, Wearable and Ubiquitous Technologies, 8, 3. https://doi.org/10.1145/3678516
Greengard, S., Virtual Reality. 2019: MIT Press.
Jacobson, B.H., Smith, D., Fronterhouse, J., Kline, C., & Boolani, A. (2012). Assessment of the benefit of powered exercises for muscular endurance and functional capacity in elderly participants, Journal of Physical Activity and Health, 9, 1030-1035. https://doi.org/10.1123/jpah.9.7.1030
Kaplan, A.D., et al., The Effects of Virtual Reality, Augmented Reality, and Mixed Reality as Training Enhancement Methods: A Meta-Analysis. Human Factors, 2021. 63(4): p. 706-726.
Kanning, M. & Schlicht, W. (2010). Be active and become happy: an ecological momentary assessment of physical activity and mood. Journal of Sport and Exercise Psychology, 32, 253-261. https://doi.org/10.1123/jsep.32.2.253
Kimura, N., Masuda, T., Ataka, T., & Matsubara, E. (2024). Relationship between measured conversation time and social behavior in community-dwelling older adults. Frontiers in Neurology, 15 https://doi.org/10.3389/fneur.2024.1479296
Kononova, A., Li, L., Kamp, K., Bowen, M., Rikard, R. V., Cotten, S., & Peng, W. (2019). The use of wearable activity trackers among older adults: focus group study of tracker perceptions, motivators, and barriers in the maintenance stage of behavior change. JMIR mHealth and uHealth, 7(4), e9832. https://doi.org/10.2196/mhealth.9832
Lee, J. Y., & Lee, S. Y. (2024). Development of AI-based predictive algorithm for early diagnosis of high-risk dementia groups among the elderly: Utilizing health lifelog data. Healthcare, 12(18), 1872. https://doi.org/10.3390/healthcare12181872
Li, J., Ma, Q., Chan, A. H., & Man, S. (2019). Health monitoring through wearable technologies for older adults: Smart wearables acceptance model. Applied Ergonomics, 75, 162-169. https://doi.org/10.1016/j.apergo.2018.10.006
Lin, Charles & Lee, Chaiwoo & Lally, Dennis & Coughlin, Joseph. (2018). Impact of Virtual Reality (VR) Experience on Older Adults’ Well-Being. 10.1007/978-3-319-92037-5_8.
Liang, P. (2024). Development of Next Generation Assistive Wearable Device. Unpublished thesis dissertation, University of Technology Sydney.
Mandal, S. Brief Introduction of Virtual Reality & its Challenges. 2013.
Martinato, M., Lorenzoni, G., Zanchi, T., et al. (2021). Usability and accuracy of a smartwatch for the assessment of physical activity in the elderly population: Observational study. JMIR mHealth and uHealth, 9(5), e20966. https://doi.org/10.2196/20966
Moore, K., O'Shea, E., Kenny, L., Barton, J., Tedesco, S., Sica, M., ... & Timmons, S. (2021). Older adults’ experiences with using wearable devices: qualitative systematic review and meta-synthesis. JMIR mHealth and uHealth, 9(6), e23832. https://doi.org/10.2196/23832
Nurmi, J., Knittle, K., Ginchev, T., Khattak, F., Helf, C., Zwickl, P., ... & Haukkala, A. (2020). Engaging users in the behavior change process with digitalized motivational interviewing and gamification: Development and feasibility testing of the PRECIOUS app. JMIR mHealth and uHealth, 8(1), e12884. https://doi.org/10.2196/12884
Olmedo-Aguirre, J. O., Reyes-Campos, J., Alor-Hernandez, G., Machorro-Cano, I., Rodriguez-Mazahua, L., & Sanchez-Cervantes, J. L. (2022). Remote healthcare for elderly people using wearables: A review. Biosensors, 12(2), 73. https://doi.org/10.3390/bios12020073
Paraschiakos, S., Cachucho, R., Moed, M. et al. Activity recognition using wearable sensors for tracking the elderly. User Modeling and User-Adapted Interaction, 30, 567–605. https://doi.org/10.1007/s11257-020-09268-2
Peng, W., Li, L., Kononova, A., Cotten, S., Kamp, K., & Bowen, M. (2021). Habit formation in wearable activity tracker use among older adults: qualitative study. JMIR mHealth and uHealth, 9(1), e22488. https://doi.org/10.2196/22488
Pichandi, K. V., Senthil, P., Prabakar, D., & Uma, S. (2025). Artificial internet of medical things for wearable body sensor data analysis. Expert Systems with Applications, 260, 125338. https://doi.org/10.1016/j.eswa.2024.125338
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Wardi, G., Nemati, S., & Nagarajan, V. (2024). 161 use of wearable data to predict emergency department revisits. Annals of Emergency Medicine. 84(4), S76. https://doi.org/10.1016/j.annemergmed.2024.08.167
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Yan, Q. S., & Guo, Q. (2024). Enhancement or Suppression? Differential Association of Digital Literacy with Subjective Health of Older Adults. Frontiers in Public Health, 12 https://doi.og/10.3389/fpubh.2024.1395162
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Moore, K., O'Shea, E., Kenny, L., Barton, J., Tedesco, S., Sica, M., ... & Timmons, S. (2021). Ervaringen van ouderen met het gebruik van draagbare apparaten: kwalitatieve systematische review en metasynthese. JMIR mHealth en uHealth, 9(6), e23832. https://doi.org/10.2196/23832
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Olmedo-Aguirre, J. O., Reyes-Campos, J., Alor-Hernandez, G., Machorro-Cano, I., Rodriguez-Mazahua, L., & Sanchez-Cervantes, J. L. (2022). Gezondheidszorg op afstand voor ouderen met behulp van wearables: een overzicht. Biosensoren, 12(2), 73. https://doi.org/10.3390/bios12020073
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Saleh Kalantari, Tong Bill Xu, Armin Mostafavi, Benjamin Kim, Andrew Dilanchian, Angella Lee, Walter R Boot, Sara J Czaja, Immersive virtual reality gebruiken om de sociale interactie tussen oudere volwassenen te verbeteren: een cross-site onderzoek, innovatie in veroudering, Volume 7, Issue 4, 2023, igad031, https://doi.org/10.1093/geroni/igad031
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van Gameren, M., Voorn, P. B., Bossen, D., et al. (2024). De Short Physical Performance Battery correleert niet met de kwaliteit en kwantiteit van het dagelijks leven bij thuiswonende oudere volwassenen met een verhoogd valrisico. Gang en houding, 114, 78-83. https://doi.org/10.1016/j.gaitpost.2024.09.005
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Wall, C., Young, F., & McMeekin, P. (2024). CuePD: een IoT-benadering voor het verbeteren van looprevalidatie bij oudere volwassenen door middel van gepersonaliseerde muziekcueing. IEEE Sensoren Journal, 8, 1-4. https://doi.org/10.1109/LSENS.2024.3456855
Wang, L.-T. (2023). Effectiviteit van virtual reality-oefeningen voor functionele fitheid bij thuiswonende oudere volwassenen: een follow-uponderzoek van 12 weken. Salie Open, 13(4). https://doi.org/10.1177/21582440231218515
Wardi, G., Nemati, S., & Nagarajan, V. (2024). 161 Gebruik van draagbare gegevens om herbezoeken van de spoedeisende hulp te voorspellen. Annalen van spoedeisende geneeskunde. 84, lid 4, S76. https://doi.org/10.1016/j.annemergmed.2024.08.167
Yan, J.H. & Zhou, C.L. (2009). Effecten van motorische praktijk op cognitieve stoornissen bij oudere volwassenen. Europese groep voor onderzoek naar ouderen en lichaamsbeweging, 6, 67-74. https://doi.org/10.1007/s11556-009-0049-6
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Chow, H. W., & Yang, C. C. (2020). Accuracy of optical heart rate sensing technology in wearable fitness trackers for young and older adults: validation and comparison study. JMIR mHealth and uHealth, 8(4), e14707. https://doi.org/10.2196/14707
Ehn, M., Eriksson, L. C., Åkerberg, N., & Johansson, A. C. (2018). Activity monitors as support for older persons’ physical activity in daily life: qualitative study of the users’ experiences. JMIR mHealth and uHealth, 6(2), e8345. https://doi.org/10.2196/mhealth.8345
Frey-Law, L. A., Merkle, S. L., Dailey, D., & Sluka, K. A. (2024). Nonlinear modification to Hildebrand equation for accelerometry assessment of physical activity: improved accuracy for low activity levels. Exploration of Musculoskeletal Diseases, 2(5), 408-422. https://doi.org/10.37349/emd.2024.00066
Fries, J.F., & Crapo, L.M. (1981). Vitality and aging. San Francisco: Freeman.
Gao, W., Du, K., Luo, Y., Shi, W., & Shi, Y. (2024). EasyAsk: An In-App Contextual Tutorial Search Assistant for Older Adults. Interactive, Mobile, Wearable and Ubiquitous Technologies, 8, 3. https://doi.org/10.1145/3678516
Greengard, S., Virtual Reality. 2019: MIT Press.
Jacobson, B.H., Smith, D., Fronterhouse, J., Kline, C., & Boolani, A. (2012). Assessment of the benefit of powered exercises for muscular endurance and functional capacity in elderly participants, Journal of Physical Activity and Health, 9, 1030-1035. https://doi.org/10.1123/jpah.9.7.1030
Kaplan, A.D., et al., The Effects of Virtual Reality, Augmented Reality, and Mixed Reality as Training Enhancement Methods: A Meta-Analysis. Human Factors, 2021. 63(4): p. 706-726.
Kanning, M. & Schlicht, W. (2010). Be active and become happy: an ecological momentary assessment of physical activity and mood. Journal of Sport and Exercise Psychology, 32, 253-261. https://doi.org/10.1123/jsep.32.2.253
Kimura, N., Masuda, T., Ataka, T., & Matsubara, E. (2024). Relationship between measured conversation time and social behavior in community-dwelling older adults. Frontiers in Neurology, 15 https://doi.org/10.3389/fneur.2024.1479296
Kononova, A., Li, L., Kamp, K., Bowen, M., Rikard, R. V., Cotten, S., & Peng, W. (2019). The use of wearable activity trackers among older adults: focus group study of tracker perceptions, motivators, and barriers in the maintenance stage of behavior change. JMIR mHealth and uHealth, 7(4), e9832. https://doi.org/10.2196/mhealth.9832
Lee, J. Y., & Lee, S. Y. (2024). Development of AI-based predictive algorithm for early diagnosis of high-risk dementia groups among the elderly: Utilizing health lifelog data. Healthcare, 12(18), 1872. https://doi.org/10.3390/healthcare12181872
Li, J., Ma, Q., Chan, A. H., & Man, S. (2019). Health monitoring through wearable technologies for older adults: Smart wearables acceptance model. Applied Ergonomics, 75, 162-169. https://doi.org/10.1016/j.apergo.2018.10.006
Lin, Charles & Lee, Chaiwoo & Lally, Dennis & Coughlin, Joseph. (2018). Impact of Virtual Reality (VR) Experience on Older Adults’ Well-Being. 10.1007/978-3-319-92037-5_8.
Liang, P. (2024). Development of Next Generation Assistive Wearable Device. Unpublished thesis dissertation, University of Technology Sydney.
Mandal, S. Brief Introduction of Virtual Reality & its Challenges. 2013.
Martinato, M., Lorenzoni, G., Zanchi, T., et al. (2021). Usability and accuracy of a smartwatch for the assessment of physical activity in the elderly population: Observational study. JMIR mHealth and uHealth, 9(5), e20966. https://doi.org/10.2196/20966
Moore, K., O'Shea, E., Kenny, L., Barton, J., Tedesco, S., Sica, M., ... & Timmons, S. (2021). Older adults’ experiences with using wearable devices: qualitative systematic review and meta-synthesis. JMIR mHealth and uHealth, 9(6), e23832. https://doi.org/10.2196/23832
Nurmi, J., Knittle, K., Ginchev, T., Khattak, F., Helf, C., Zwickl, P., ... & Haukkala, A. (2020). Engaging users in the behavior change process with digitalized motivational interviewing and gamification: Development and feasibility testing of the PRECIOUS app. JMIR mHealth and uHealth, 8(1), e12884. https://doi.org/10.2196/12884
Olmedo-Aguirre, J. O., Reyes-Campos, J., Alor-Hernandez, G., Machorro-Cano, I., Rodriguez-Mazahua, L., & Sanchez-Cervantes, J. L. (2022). Remote healthcare for elderly people using wearables: A review. Biosensors, 12(2), 73. https://doi.org/10.3390/bios12020073
Paraschiakos, S., Cachucho, R., Moed, M. et al. Activity recognition using wearable sensors for tracking the elderly. User Modeling and User-Adapted Interaction, 30, 567–605. https://doi.org/10.1007/s11257-020-09268-2
Peng, W., Li, L., Kononova, A., Cotten, S., Kamp, K., & Bowen, M. (2021). Habit formation in wearable activity tracker use among older adults: qualitative study. JMIR mHealth and uHealth, 9(1), e22488. https://doi.org/10.2196/22488
Pichandi, K. V., Senthil, P., Prabakar, D., & Uma, S. (2025). Artificial internet of medical things for wearable body sensor data analysis. Expert Systems with Applications, 260, 125338. https://doi.org/10.1016/j.eswa.2024.125338
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Yang, Q., Mamun, A. A., Wu, M., & Naznen, F. (2024). Strengthening health monitoring: Intention and adoption of IoT-enabled wearable healthcare devices. Digital Health, 10, https://doi.org/10.1177/2055207624127919
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Pichandi, K. V., Senthil, P., Prabakar, D., & Uma, S. (2025). Artificial internet of medical things for wearable body sensor data analysis. Expert Systems with Applications, 260, 125338. https://doi.org/10.1016/j.eswa.2024.125338
Ramalho A, Duarte-Mendes P, Paulo R, Serrano J, Petrica J. Crossing the digital frontier: are older adults ready for virtual reality workouts? Front Public Health. 2024 Feb 8;12:1324004. doi: 10.3389/fpubh.2024.1324004. PMID: 38389949; PMCID: PMC10881650.
Rose, D. J. & Skelton, D. A. (2019). The field of Gerokinesiology. In D. J. Rose (Ed.), Physical activity instruction of older adults (2nd ed.), pp. 1-15. Champaign IL: Human Kinetics.
Saleh Kalantari, Tong Bill Xu, Armin Mostafavi, Benjamin Kim, Andrew Dilanchian, Angella Lee, Walter R Boot, Sara J Czaja, Using Immersive Virtual Reality to Enhance Social Interaction Among Older Adults: A Cross-Site Investigation, Innovation in Aging, Volume 7, Issue 4, 2023, igad031, https://doi.org/10.1093/geroni/igad031
Teixeira, E., Fonseca, H., Diniz-Sousa, F., Veras, L., et al. (2021). Wearable devices for physical activity and healthcare monitoring in elderly people: A critical review. Geriatrics, 6, 38. https://doi.org/10.3390/geriatrics6020038
The Role of Virtual Reality in Promoting Healthy Aging and Active Lifestyles | FXMedia: Solutions for Metaverse. (2024). Fxmweb.com. https://www.fxmweb.com/insights/the-role-of-virtual-reality-in-promoting-healthy-aging-and-active-lifestyles.html
van Gameren, M., Voorn, P. B., Bossen, D., et al. (2024). The Short Physical Performance Battery does not correlate with daily life gait quality and quantity in community-dwelling older adults with an increased fall risk. Gait & Posture, 114, 78-83. https://doi.org/10.1016/j.gaitpost.2024.09.005
Vargemidis, D., Gerling, K., Spiel, K., Abeele, V. V., & Geurts, L. (2020). Wearable physical activity tracking systems for older adults—a systematic review. ACM Transactions on Computing for Healthcare, 1(4), 1-37. https://doi.org/10.1145/3402523
Wall, C., Young, F., & McMeekin, P. (2024). CuePD: An IoT Approach for Enhancing Gait Rehabilitation in Older Adults through Personalized Music Cueing. IEEE Sensors Journal, 8, 1-4. https://doi.org/10.1109/LSENS.2024.3456855
Wang, L.-T. (2023). Effectiveness of Virtual Reality Exercise for Functional Fitness in Community-Dwelling Older Adults: A 12-Week Follow-Up Study. Sage Open, 13(4). https://doi.org/10.1177/21582440231218515
Wardi, G., Nemati, S., & Nagarajan, V. (2024). 161 use of wearable data to predict emergency department revisits. Annals of Emergency Medicine. 84(4), S76. https://doi.org/10.1016/j.annemergmed.2024.08.167
Yan, J.H. & Zhou, C.L. (2009). Effects of motor practice on cognitive disorders in older adults. European Group for Research into Elderly and Physical Activity, 6, 67-74. https://doi.org/10.1007/s11556-009-0049-6
Yan, Q. S., & Guo, Q. (2024). Enhancement or Suppression? Differential Association of Digital Literacy with Subjective Health of Older Adults. Frontiers in Public Health, 12 https://doi.og/10.3389/fpubh.2024.1395162
Yang, Q., Mamun, A. A., Wu, M., & Naznen, F. (2024). Strengthening health monitoring: Intention and adoption of IoT-enabled wearable healthcare devices. Digital Health, 10, https://doi.org/10.1177/2055207624127919