Background: The rapid development of technology such as sensors and artificial intelligence in recent years enables monitoring frailty criteria to assess frailty early and accurately from a remote location such as a home. However, research shows technologies being abandoned or rejected by users due to a lack of compatibility and consumer involvement in selecting their assistive technology devices. This study aims to understand older adults’ perceptions and preferences of technologies that can potentially assess frailty at home. Methods: This study collected qualitative data through focus group meetings with 15 participants ages 65 and older. Researchers asked participants questions to achieve the goal of understanding their attitudes on the technologies. These questions include (1) the concerns or barriers of installing and using the presented technology in daily life at home, (2) the reasons participants like or dislike a particular technology, (3) what makes a specific technology more acceptable, and (4) participants’ preferences in choosing technologies. Data were transcribed, coded and categorized, and finally synthesized to understand the attitudes towards presented technologies. Results: Three focus group sessions were conducted with five participants in each session. In the findings, the attitudes and perspectives of participants on the technologies for assessing frailty were categorized into four themes: (A) general attitude towards using the technologies, (B) conditions for accepting certain technologies, (C) existing living habits or patterns related to using the technologies, and (D) constructive suggestions related to the technologies. Conclusions: Participants generally had positive attitudes towards allowing the technologies to be installed and used at their homes. They would accept some technologies if used under certain conditions. However, questions and concerns remain, such as concerns about privacy, functionality, and aesthetics. The study also found that older adults’ living habits or patterns could affect the design and use of technology. Lastly, many valuable suggestions have been made by participants. These perspectives and insights can help improve the design and adoption of home-based frailty assessment technologies among older adults.

Early identification of frailty is crucial to prevent or reverse its progression but faces challenges due to frailty’s insidious onset. Monitoring behavioral changes in real life may offer opportunities for the early identification of frailty before clinical visits. This study presented a sensor-based system that used heterogeneous sensors and cloud technologies to monitor behavioral and physical signs of frailty from home settings. We aimed to validate the concurrent validity of the sensor measurements. The sensor system consisted of multiple types of ambient sensors, a smart speaker, and a smart weight scale. The selection of these sensors was based on behavioral and physical signs associated with frailty. Older adults’ perspectives were also included in the system design. The sensor system prototype was tested in a simulated home lab environment with nine young, healthy participants. Cohen’s Kappa and Bland–Altman Plot were used to evaluate the agreements between the sensor and ground truth measurements. Excellent concurrent validity was achieved for all sensors except for the smart weight scale. The bivariate correlation between the smart and traditional weight scales showed a strong, positive correlation between the two measurements (r = 0.942, n = 24, p < 0.001). Overall, this work showed that the Frailty Toolkit (FT) is reliable for monitoring physical and behavioral signs of frailty in home settings.

Background The rapid development of technology such as sensors and artificial intelligence in recent years enables monitoring frailty criteria to assess frailty early and accurately from a remote location such as a home. However, research shows technologies being abandoned or rejected by users due to a lack of compatibility and consumer involvement with the technologies. This study aims to understand older adult’s perceptions and preferences of technologies that can be potentially used to assess frailty in home settings. Methods This study is a qualitative study in which data were collected through focus group interviews. We recruited 15 older participants. Questions were asked to achieve the goal of understanding their attitudes on the technologies. These questions include 1) the concerns or barriers of installing and using the presented technology in daily life at home, 2) the reasons participants like or dislike a particular technology, 3) what makes a particular technology more acceptable, and 4) participants’ preferences in choosing technologies. Data were transcribed, coded and categorized, and finally synthesized to understand the attitudes towards presented technologies.Results A total of 15 older adults aged 65 and older were recruited. Three focus group sessions were conducted with five participants in each session. In the findings, the attitudes and perspectives of participants on the technologies for assessing frailty were presented in four areas: A) general attitude towards using the technologies, B) concerns about the technologies, C) existing living habits or patterns related to using the technologies, and D) constructive suggestions related to the technologies.Conclusions This study focuses on understanding the attitudes and perceptions of older adults on several technologies that could potentially be used to assess frailty in home settings. Participants generally have positive attitudes towards allowing the technologies to be installed and used at their home. Some technologies were found to be more acceptable if used under certain conditions. However, questions and concerns still remain. The study also found the living habits or patterns of older adults could affect the design and use of technology. Lastly, many valuable suggestions have been made by participants.

BackgroundEarly identification of frailty is crucial to prevent or reverse the syndrome but faces challenges due to frailty’s insidious onset. Monitoring behaviroal changes in real life may offer opportunities for early identifying frailty. Home-based technologies for assessing frailty have shown potentials. However, they are still in early stage of development with many types of technologies and behavioural and physical signs associated with frailty underexamined. This study presented a sensor-based system that used heterogeneous sensors and cloud technologies to monitor behavioural and physical signs of frailty from home settings. We aimed to validate the concurrent validity of the sensor system.MethodsThe sensor system consisted of motion, door, distance and mat sensors, a smart speaker, and a smart weight scale. The selection of these sensors was based on behavioural and physical signs found significantly associated with frailty. These signs included room-level physical activity, life space, sedentary behaviour, stair climbing, self-report exhaustion, and weight. Older adults’ voices were included in the system design. The sensor system prototype was tested in a simulated home lab environment with nine young, healthy participants. Cohen’s kappa and Bland-Altman Plot statistical methods evaluated the agreements between the sensor and ground truth measurements.ResultsExcellent concurrent validity was achieved for the smart speaker (100% agreement), the motion sensor (a kappa value of k=0.938), the door sensor (87.5% agreement, 100% if excluding outliers), the mat sensor (mean difference of -0.286, 95% limits of agreement) and the distance sensor (mean difference of 0.526, 95% limits of agreement). The smart weight scale and traditional weight scale had a significant difference in weight measurements. However, bivariate correlation showed a strong, positive correlation between the two measurements (r=0.942, n=24, p<0.001). ConclusionsOverall, FT is reliable for monitoring physical and behavioural signs of frailty in home settings. The ambient sensors and the smart speaker in FT showed excellent concurrent validity, while the smart weight scale needs further validation. This work laid the ground for the next step of the research to test the toolkit with frail and non-frail older adults to validate the system’s clinical effectiveness.