Frailty is an age-related condition characterized by a decline in physical capacity with an increased vulnerability to stressors. During the COVID-19 pandemic, there was considerable progression in frailty in older adults. Therefore, an online frailty check (FC) is required for continuous screening, especially acceptable to older adults. We aimed to co-design/co-develop an online FC application with FC supporters who were facilitators in a pre-existing onsite FC program in the community. It consisted of a self-assessment of sarcopenia and an 11-item questionnaire assessing dietary, physical, and social behaviors. Opinions obtained from FC supporters (median 74.0 years) were categorized and implemented. The usability was assessed using the system usability scale (SUS). For both FC supporters and participants (n = 43), the mean score was 70.2 ± 10.3 points, which implied a “marginally high” acceptability and a “good” adjective range. Multiple regression analysis showed that the SUS score was significantly correlated with onsite–online reliability, even after adjusting for age, sex, education level, and ICT proficiency (b = 0.400, 95% CI: 0.243–1.951, p = 0.013). We also validated the online FC score, which showed a significant association between onsite and online FC scores (R = 0.670, p = 0.001). In conclusion, the online FC application is an acceptable and reliable tool to check frailty for community-dwelling older adults.

Population aging leads to more expensive social security and medical care in a society. In order to minimize national expenditure dedicated to providing support to the elderly, it is necessary to reduce the cost of treatment. Current prophylactic approaches mainly include training programs tailored towards seniors, who may be assisted by caregivers, for wellness maintenance and enhancement. However, these approaches are mainly administered by volunteers, who are often overburdened because of labor shortages. It is thus necessary to design and implement a system that enables seniors to maintain and improve their health by themselves. In this study, we propose and test a smartphone-based gait measurement application. Our results indicate that the mobile application can help motivate seniors to walk more regularly and improve their walking ability. Moreover, we found in our experiments that since our application helped improve our senior subjects’ physical fitness, some of them became interested in participating in social activities and using new technologies as a consequence.

The ability of individuals with visual impairment to recognize an obstacle by hearing is called “obstacle sense”. This ability is facilitated while they are moving, though the exact reason remains unknown. This study aims to clarify which acoustical factors may contribute to obstacle sense, especially obstacle distance perception. First, we conducted a comparative experiment regarding obstacle distance localization by individuals who are blind (N = 5, five men with blindness aged 22–42 (average: 29.8)) while they were standing and walking. The results indicate that the localized distance was more accurate while walking than while standing. Subsequently, the head rotation angle while walking and acoustic characteristics with respect to obstacle distance and head rotation angle were investigated. The peaks of the absolute head rotation angle during walking ranged from 2.78° to 11.11° (average: 6.55°, S.D.: 2.05°). Regarding acoustic characteristics, acoustic coloration occurred, and spectral interaural differences and interaural intensity differences were observed in the blind participants (N = 4, four men including two blind and two control sighted persons aged 25–38 (average: 30.8)). To determine which acoustic factors contribute, we examined the threshold of changes for interaural differences in time (ITD) and intensity (IID) (N = 11, seven men and four women with blindness aged 21–35 (average: 27.4)), as well as coloration (ICD) (N = 6, seven men and a woman with blindness aged 21–38 (average: 29.9))—depending on the head rotation. Notably, ITD and IID thresholds were 86.2 μs and 1.28 dB; the corresponding head rotation angles were 23.5° and 9.17°, respectively. The angle of the ICD threshold was 6.30° on average. Consequently, IID might be a contributing factor and ICD can be utilized as the cue facilitating the obstacle distance perception while walking.

Frailty, an age-related decline in homeostatic reserves, markedly proceeded during the coronavirus disease 2019 pandemic. To continuously assess frailty status, a remote system is urgently required. We aimed to co-design/co-develop an online frailty check (FC) application alongside FC supporters who were facilitators in a pre-existing onsite FC program. The online FC included a screening measurement for sarcopenia and an 11-item questionnaire covering dietary, physical, and social behaviors. Using prototype applications, 55 opinions obtained from 32 FC supporters (median 74.0 years) were categorized and reflected refinement. Regarding the self-efficacy of FC supporters, a significant increase in social positioning was seen after the mock test (P=.031). For FC supporters and participants, the average system usability scale (SUS) score was 70.2±10.3 points, which was “marginally high” for acceptability and “good” for the adjective range. Multiple regression analysis showed that the SUS score was significantly correlated with online-onsite reliability but not online communication, even after adjusting by age, sex, education level, and ICT proficiency (b=0.400, 95% CI: 0.243-1.951, P=.013). Additionally, a significant association between onsite and online FC scores was observed (R=0.670, P=.001). Our online FC application was evaluated to be a valuable tool to practically assess frailty status remotely.

In the current era of AI technology, where systems increasingly rely on big data to process vast amounts of societal information, efficient methods for integrating and utilizing diverse datasets are essential. This article presents a novel approach for transforming the feature space of different datasets through singular value decomposition (SVD) to extract common and hidden features as using the prior domain knowledge. Specifically, we apply this method to two datasets: 1) one related to physical and cognitive frailty in the elderly; and 2) another focusing on identifying IKIGAI (happiness, self-efficacy, and sense of contribution) in volunteer staff of a civic health promotion activity. Both datasets consist of multiple sub-datasets measured using different modalities, such as facial expressions, sound, activity, and heart rates. By defining feature extraction methods for each subdataset, we compare and integrate the overlapping data. The results demonstrated that our method could effectively preserve common characteristics across different data types, offering a more interpretable solution than traditional dimensionality reduction methods based on linear and nonlinear transformation. This approach has significant implications for data integration in multidisciplinary fields and opens the door for future applications to a wide range of datasets.