Care rehab tech company Rehab completes online and AI-based frailty prevention demonstration experiment in 3 municipalities in Aichi Prefecture—Approx. 90% of participants show satisfaction and intention to continue
Rehab for JAPAN completed an online/AI-based frailty prevention experiment in 3 Aichi municipalities. Combining online rehab with AI motion analysis, approx. 90% of elderly participants showed satisfaction and a desire to continue.
📋 Article Processing Timeline
- 📰 Published: April 23, 2026 at 19:00
- 🔍 Collected: April 23, 2026 at 10:31
- 🤖 AI Analyzed: April 23, 2026 at 14:20 (3h 48m after Collected)
Rehab for JAPAN Inc. (Headquarters: Tokyo, CEO: Ryo Okubo, hereinafter "Rehab") conducted a demonstration experiment on "new frailty prevention utilizing online and AI technologies" in three municipalities in Aichi Prefecture (Ama City, Inazawa City, and Obu City) from October 2025 to January 2026, and has now compiled the results.
This demonstration experiment targets seniors aged 65 and over, providing an optimal exercise program utilizing online gymnastics—conducted while communicating with remote trainers via monitors—and a tool that uses AI to analyze participants' movement data for physical evaluation.
As a result of the demonstration experiment, approximately 90% of the participants expressed satisfaction and a desire to continue, with comments such as "I was able to exercise just as well as in-person" and "The quality of the exercise is high because we can converse interactively even through a screen."
Significance of this initiative and overview of the demonstration
In Aichi Prefecture, as the number of late-stage elderly rapidly increases leading up to 2025, initiatives for frailty prevention have become an urgent task. However, the traditional face-to-face "care prevention exercise classes" face limitations in terms of provision opportunities and content, such as high participation hurdles for seniors with mobility difficulties and challenges in securing instructors, resulting in the issue of not being able to sufficiently expand daily exercise opportunities for seniors.
To solve these issues, in this demonstration experiment from October 2025 to January 2026, a "Hybrid Care Prevention Class" combining the online rehabilitation service "Rehab Studio" and the AI motion analysis tool "Rehab Cloud Motion AI" was conducted for seniors in 3 municipalities (average age 78, total of 26 participants) jointly with Generous Inc. (President and CEO: Tatsuki Koyama, hereinafter "Generous"), a care business operator based in Aichi Prefecture.
In addition to traditional face-to-face exercise instruction, two formats were introduced: "Facility Assembly Online," where rehabilitation professionals provide real-time exercise instruction through a TV monitor at the venue, and "Home Participation Online," where participants join using a tablet device from their homes. A total of 8 to 9 classes (60 minutes per session) were held in each municipality. Furthermore, during the first and final sessions, physical function measurements (one-leg standing, 5-time sit-to-stand) were conducted using Motion AI to objectively grasp the effects of the initiative.
For details, please refer to the demonstration launch releases in each municipality.
Ama City: https://prtimes.jp/main/html/rd/p/000000126.000027102.html
Inazawa City: https://prtimes.jp/main/html/rd/p/000000128.000027102.html
Obu City: https://prtimes.jp/main/html/rd/p/000000129.000027102.html
Scenes from the demonstration experiment
Main achievements of the demonstration experiment
Both satisfaction and intention to continue among participants are at about 90%
In the post-demonstration survey, the total number of "very satisfied" and "mostly satisfied" responses for both facility assembly and home participation formats reached about 90% of the total. Comments included "I was able to exercise just as well as in-person," "Looking through the screen was refreshing and enjoyable," "The quality of the exercise is high because I can converse interactively with the coach from home," and "During oral gymnastics, I spoke louder than usual because I was voicing out towards the teacher on the screen." Regarding the intention to continue, about 90% for both formats answered that they "want to participate."
Visualizing achievements with Motion AI
In the AI physical function measurements conducted before and after the classes, many participants maintained their scores and seconds for the 5-time sit-to-stand, and seconds and balance evaluation (FRS) for the one-leg stand, with some showing improvement. Many participants commented, "It gave me a chance to objectively know my body's condition" and "I became more conscious of my posture than usual," demonstrating that AI physical evaluations encourage behavioral changes in the seniors themselves. Slightly less than 20% of the participants answered that they "increased opportunities to move their bodies in daily life," suggesting that the exercises in the class are leading to daily habituation.
Issues solved by the introduction
In response to issues faced by traditional face-to-face classes, such as "participants' travel burden and participation hurdles," "shortage of instructors," and "grasping business outcomes," the hybrid care prevention class brings the following effects.
Expansion of participants: By making it possible to participate from home, it reaches seniors who have difficulty traveling and residents who have returned their driver's licenses.
Improvement in event frequency: The online provision system enables efficient expansion of involvement with seniors using fewer professionals.
Cost control: Reduces trainers' travel costs and realizes quantitative expansion of care prevention services while controlling costs through simultaneous connection of multiple classes, etc.
Quantitative understanding of outcomes: The effectiveness of the business is evaluated with objective data through pre- and post-evaluations of physical functions using Motion AI.
This demonstration experiment targets seniors aged 65 and over, providing an optimal exercise program utilizing online gymnastics—conducted while communicating with remote trainers via monitors—and a tool that uses AI to analyze participants' movement data for physical evaluation.
As a result of the demonstration experiment, approximately 90% of the participants expressed satisfaction and a desire to continue, with comments such as "I was able to exercise just as well as in-person" and "The quality of the exercise is high because we can converse interactively even through a screen."
Significance of this initiative and overview of the demonstration
In Aichi Prefecture, as the number of late-stage elderly rapidly increases leading up to 2025, initiatives for frailty prevention have become an urgent task. However, the traditional face-to-face "care prevention exercise classes" face limitations in terms of provision opportunities and content, such as high participation hurdles for seniors with mobility difficulties and challenges in securing instructors, resulting in the issue of not being able to sufficiently expand daily exercise opportunities for seniors.
To solve these issues, in this demonstration experiment from October 2025 to January 2026, a "Hybrid Care Prevention Class" combining the online rehabilitation service "Rehab Studio" and the AI motion analysis tool "Rehab Cloud Motion AI" was conducted for seniors in 3 municipalities (average age 78, total of 26 participants) jointly with Generous Inc. (President and CEO: Tatsuki Koyama, hereinafter "Generous"), a care business operator based in Aichi Prefecture.
In addition to traditional face-to-face exercise instruction, two formats were introduced: "Facility Assembly Online," where rehabilitation professionals provide real-time exercise instruction through a TV monitor at the venue, and "Home Participation Online," where participants join using a tablet device from their homes. A total of 8 to 9 classes (60 minutes per session) were held in each municipality. Furthermore, during the first and final sessions, physical function measurements (one-leg standing, 5-time sit-to-stand) were conducted using Motion AI to objectively grasp the effects of the initiative.
For details, please refer to the demonstration launch releases in each municipality.
Ama City: https://prtimes.jp/main/html/rd/p/000000126.000027102.html
Inazawa City: https://prtimes.jp/main/html/rd/p/000000128.000027102.html
Obu City: https://prtimes.jp/main/html/rd/p/000000129.000027102.html
Scenes from the demonstration experiment
Main achievements of the demonstration experiment
Both satisfaction and intention to continue among participants are at about 90%
In the post-demonstration survey, the total number of "very satisfied" and "mostly satisfied" responses for both facility assembly and home participation formats reached about 90% of the total. Comments included "I was able to exercise just as well as in-person," "Looking through the screen was refreshing and enjoyable," "The quality of the exercise is high because I can converse interactively with the coach from home," and "During oral gymnastics, I spoke louder than usual because I was voicing out towards the teacher on the screen." Regarding the intention to continue, about 90% for both formats answered that they "want to participate."
Visualizing achievements with Motion AI
In the AI physical function measurements conducted before and after the classes, many participants maintained their scores and seconds for the 5-time sit-to-stand, and seconds and balance evaluation (FRS) for the one-leg stand, with some showing improvement. Many participants commented, "It gave me a chance to objectively know my body's condition" and "I became more conscious of my posture than usual," demonstrating that AI physical evaluations encourage behavioral changes in the seniors themselves. Slightly less than 20% of the participants answered that they "increased opportunities to move their bodies in daily life," suggesting that the exercises in the class are leading to daily habituation.
Issues solved by the introduction
In response to issues faced by traditional face-to-face classes, such as "participants' travel burden and participation hurdles," "shortage of instructors," and "grasping business outcomes," the hybrid care prevention class brings the following effects.
Expansion of participants: By making it possible to participate from home, it reaches seniors who have difficulty traveling and residents who have returned their driver's licenses.
Improvement in event frequency: The online provision system enables efficient expansion of involvement with seniors using fewer professionals.
Cost control: Reduces trainers' travel costs and realizes quantitative expansion of care prevention services while controlling costs through simultaneous connection of multiple classes, etc.
Quantitative understanding of outcomes: The effectiveness of the business is evaluated with objective data through pre- and post-evaluations of physical functions using Motion AI.