Multi-disciplinary Design and In-Home Evaluation of Kinect-Based Exercise Coaching System for Elderly (original) (raw)
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Design and Evaluation of an Interactive Exercise Coaching System for Older Adults: Lessons Learned
Although the positive effects of exercise on the well-being and quality of independent living for older adults are well-accepted, many elderly individuals lack access to exercise facilities, or the skills and motivation to perform exercise at home. To provide a more engaging environment that promotes physical activity, various fitness applications have been proposed. Many of the available products, however, are geared toward a younger population and are not appropriate or engaging for an older population. To address these issues, we developed an automated interactive exercise coaching system using the Microsoft Kinect. The coaching system guides users through a series of video exercises, tracks and measures their movements, provides real-time feedback, and records their performance over time. Our system consists of exercises to improve balance, flexibility, strength, and endurance, with the aim of reducing fall risk and improving performance of daily activities. In this paper, we report on the development of the exercise system, discuss the results of our recent field pilot study with six independently-living elderly individuals, and highlight the lessons learned relating to the in-home system setup, user tracking, feedback, and exercise performance evaluation.
Design and Implementation of an Antagonistic Exercise Support System Using a Depth Image Sensor
EAI Endorsed Transactions on Pervasive Health and Technology, 2017
Dementia is one of the main reasons for elderly people becoming dependent on care. Antagonistic exercise, which involves performing different movements with the upper and lower limbs on the left and right sides, is a form of exercise that uses cognitive and motor functions at the same time. Preventive care professionals who can lead this sort of exercise are few in number compared with elderly people, and are under a heavy burden. On the other hand, the Kinect has become popular as a low-cost device that can acquire human actions. In this study we designed and implemented an antagonistic exercise support system using a Kinect. The user's joint information acquired from Kinect is used to estimate the exercise, and the system provides real-time feedback to the user. We performed recognition accuracy tests with young and elderly test subjects, and carried out an interview survey to ascertain elderly user opinions.
A Kinect-based rehabilitation exercise monitoring and guidance system
2014 IEEE 5th International Conference on Software Engineering and Service Science, 2014
In this paper, we describe the design and implementation of a Kinect-based system for rehabilitation exercises monitoring and guidance. We choose to use the Unity framework to implement our system because it enables us to use virtual reality techniques to demonstrate detailed movements to the patient, and to facilitate examination of the quality and quantity of the patient sessions by the clinician. The avatar-based rendering of motion also preserves the privacy of the patients, which is essential for healthcare systems. The key contribution of our research is a rule-based approach to realtime exercise quality assessment and feedback. We developed a set of basic rule elements that can be used to express the correctness rules for common rehabilitation exercises.
2021
Background: Declines in physical and cognitive functions are recognized as important risk factors for falls in older adults. Promising evidence suggests that interactive game-based systems that allow simultaneous physical and cognitive exercise are a potential approach to enhance exercise adherence and reduce fall risk in older adults. However, a limited number of studies have reported the development of a combined physical-cognitive game-based training system for fall risk reduction in older adults. Objective: The aim of this study is to develop and evaluate the usability of an interactive physical-cognitive game-based training system (game-based exercise) for older adults. Methods: In the development phase (Part I), a game-based exercise prototype was created by integrating knowledge and a literature review as well as brainstorming with experts on effective fall prevention exercise for older adults. The output was a game-based exercise prototype that covers crucial physical and cognitive components related to falls. In the usability testing (Part II), 5 games (ie, Fruits Hunter, Where Am I?, Whack a Mole, Sky Falls, and Crossing Poison River) with three difficulty levels (ie, beginner, intermediate, and advanced levels) were tested in 5 older adults (mean age 70.40 years, SD 5.41 years). After completing the games, participants rated their enjoyment level while engaging with the games using the Physical Activity Enjoyment Scale (PACES) and commented on the games. Descriptive statistics were used to describe the participants' characteristics and PACES scores. Results: The results showed that the average PACES score was 123 out of 126 points overall and between 6.66 and 7.00 for each item, indicating a high level of enjoyment. Positive feedback, such as praise for the well-designed interactions and user-friendly interfaces, was also provided. Conclusions: These findings suggest that it is promising to implement an interactive, physical-cognitive game-based exercise in older adults. The effectiveness of a game-based exercise program for fall risk reduction has yet to be determined.
Open Journal of Therapy and Rehabilitation, 2014
Purpose: Elderly persons may benefit from regular physical exercise to maintain or improve their quality of life and health status. Low adherence to physical exercise, however, is often a problem. A new type of videogames, "exergames", involving physical motion of the players has recently been developed and is expected to keep elderly people active. The purpose of this study is to examine the effect of a newly developed exergame on health benefits such as muscle strength and body balance of elderly people. Methods: We invited 24 healthy community-dwelling elderly persons aged 71.46 ± 4.8 years old (8 men and 16 women) volunteered for this study. We developed a new exergame program for using Kinect TM (Microsoft Co., Ltd. Redmond, WA) motion sensor. A single exergame session lasted approximately 30 minutes including warm-up and cool-down sessions. The participants are asked to play the exergame 2 -3 times per week for 2.5 months at our institute. Maximal isometric muscular strength of major muscles of lower extremities and functional balance were examined before and after the exergame intervention. Result: All participants completed 24 sessions of the exergame program. There were significant improvements in maximal isometric muscular strength of hip joint flexion, and knee joint extension and flexion, of ankle joint dorsiflexion. Also MFC, a significant difference was noted between Pre and Post values. However, there was no statistically sig-nificant improvement in the functional balance test. Conclusion: Exergame developed in this study was found to be effective in improving muscular strength of lower extremities.
Revista de Fisioterapia, 2021
The present study aims to describe the efficacy of Kinect technology for the therapeutic rehabilitation of geriatric patients by conducting and analyzing a 8-session therapeutic program based on this technology in which 12 study subjects participated, 8 Male subjects and 4 female subjects, within the physical capacities, the muscular strength was evaluated in the Daniels scale of the flexion of the hip, knee, shoulder and elbow and the goniometry of the flexion / extension of these same members. A greater elasticity and mobility were observed by female subjects apart from a greater increase in the range of motion in the same period of time than Male subjects, with respect to muscle strength, it was not possible to demonstrate a significant advance so the effectiveness of Kinect therapy in this area still shows contrasts in its results. Objective: to describe the efficacy of kinect technology for the therapeutic rehabilitation of elderly patients by carrying out and analyzing a thera...
International Journal of Virtual Worlds and Human Computer Interaction, 2014
The purpose of this research was to design, develop and assess the usability of an interactive rehabilitation game. User centered design in combination with serious gaming strategies were employed in the design of a targeted therapy programme to encourage at home balance retraining using specifically designed software with the Microsoft Kinect sensor. The development of this game involved a multidisciplinary iterative design method employing the skills of physiotherapists, engineers and participants. Preliminary testing was conducted with younger adults and more formal testing with older participants to evaluate usability. Integrating the knowledge of all stakeholders increased the acceptability of the game by older participants. All were confident in the use of the technology and keen to increase their participation. Participants indicated on a usability questionnaire that these games are more engaging than typical therapy exercises. The games can be performed at home without the requirement for a partner and the participant can increase the game complexity depending on personal needs and preference. The time that the individual spends participating in the program and the results over several sessions can also be observed by the therapist allowing a better indication of adherence to therapy than self-report.
“Was it easy”? “Yes”. “Will you use it”? “No”. Elderly Trying Out a Kinect Interface
2017
This paper describes a qualitative study that seeks to give a rich description of the experiences and viewpoints of elderly about their use of digital technologies in general and videoconferencing in particular. Interviews and workshops were methods for data collection. The workshops included a discussion group session in addition to a session of trying out gesturing as a response to a videoconference call. A prototype of a gestures-based interface for interacting with a videoconference system intended for use in their homes was tried out. The participants had clear views of technologies they used and liked, and they wanted to maintain physical fitness as long as possible. Although they found the gestures easy to perform, they did not want to use this technology in their homes. This apparent self-contradictory response is discussed. Keywords-elderly; videoconference; gestures; Kinect; design.
An Analysis of Human Motion Detection Systems Use During Elder Exercise Routines
Human motion analysis provides motion pattern and body pose estimations. This study integrates computer-vision techniques and explores a markerless human motion analysis system. Using human-computer interaction (HCI) methods and goals, researchers use a computer interface to provide feedback about range of motion to users. A total of 35 adults aged 65 and older perform three exercises in a public gym while human motion capture methods are used. Following exercises, participants are shown processed human motion images captured during exercises on a customized interface. Standardized questionnaires are used to elicit responses from users during interactions with the interface. A matrix of HCI goals (effectiveness, efficiency, and user satisfaction) and emerging themes are used to describe interactions. Sixteen users state the interface would be useful, but not necessarily for safety purposes. Users want better image quality, when expectations are matched satisfaction increases, and unclear meaning of motion measures decreases satisfaction.
This work presents a dataset of functional fitness tests acquired with Kinect v2 and physiological sensors. The dataset contains both young and senior subjects executing a number of fitness tests meeting scientific standards of reliability and validity. The main objective is the ability to assess lower-body strength, endurance, gait speed, agility and balance from the data obtained from commercially accessible devices. The dataset can be used to develop algorithms to automate the assessment of fitness levels in low-cost computer based systems for use at home, gymnasiums or care centers.