Motion-Sensing Based Management System for Smart Context-Awareness Rehabilitation Healthcare ()
1. Introduction
The cerebellum is a crucial part of the central nervous system, coordinating our movements, regulating the muscle tension, and controlling posture and gait. Various symptoms of uncoordinated movement and imbalance—indicative of spinocerebellar atrophy appear when pathological changes occur in the cerebellum. The official term for this disorder proposed by the Department of Health, Taiwan is spinocerebellar ataxia (SCA). Following onset, patients with SCA walk unsteadily (similar to a penguin); therefore, they are also termed “penguin family”. SCA, which is among a group of genetic disorders, is primarily characterized by progressive incoordination of gait, and associated with poor coordination of hands, speech, and eye movements. One study indicated that Tai Chi helps improve the unsteady gait of patients with Parkinson’s disease [1]. Hence, one of the hospitals in Taiwan attempted to improve the unsteady gait of SCA patients using medicine along with Tai Chi. Each week, volunteer professional instructors provided Tai Chi lessons to these patients at the hospital, allowing the patients to relieve emotional stress and simultaneously increase interaction between patients.
Based on this example, physical therapists may develop personalized home-based Balance Tai Chi rehabilitation exercise programs. By implementing Balance Tai Chi exercise prescriptions, patients are enabled to understand the effect that this exercise has on their physiological conditions and, with sufficient awareness, continue this exercise at home by themselves. Currently, tracking of patients prescribed with home-based balance exercises occurs weekly when they return to the hospital to practice the exercises. Thus, no objective and instant information is available as a basis for the hospital to evaluate the patients’ balance status.
Under the rehabilitation model described previously, the existing traditional balance rehabilitation training must continue at the hospital under the supervision of a professional case manager. The rehabilitation exercises are constantly repeated, which become dull. Therefore, it is difficult for many patients to practice rehabilitation exercises according to the instructions of the Tai Chi coach at home, apart from problems regarding the correctness of the posture and the control of exercise duration and intensity. Patients are required to return to the hospital for rehabilitation follow-up once a week; however, transportation and caregivers’ availability is another issue. In addition, the amount of time that the case managers are available may also be limited, because they can only assist 1 - 2 patients concurrently. These factors affect the patients’ willingness to continue and comply with their exercise prescriptions, often causing a deterioration of their symptoms that forces them to be re-admitted; consequently, medical resource utilization and burdens on the patients and their families increase [2].
Many existing studies have suggested introducing technology to improve patients’ willingness to undergo rehabilitation. Videogames can be leveraged as a telehealth technology [3]. Telehealth technology is gaining attention as a promising strategy for acquiring accurate, reliable, and time-critical health marker data, reducing health care costs, empowering patients, and promoting disease self-management with resultant improved healthcare outcomes. Although telehealth technologies provide opportunities, several barriers relating to the acceptance and use by patient, caregiver, clinical support networks include problems in use of technology among older adults, lack of adequate training or support, lack of consensus on the value of the technology, and absence of adequate technology infrastructure [4].
To overcome these barriers, it will be important for designers of telehealth technologies to work closely with specific patients throughout the design and development process in order to learn how their capabilities relate to technology adoption and long-term use [3,5]. Videogames have already been proven to improve cognitive abilities, displaying a feasible alternative to more traditional aerobic exercise for middle-aged and older adults, and can be used to train stepping ability in older adults to reduce the risk of falls [6]. The use of Wii Sports and Wii Fit has been reported in an increasing number of studies involving people with motor deficits resulting from other causes such as balance and mobility in people with some diseases [7,8].
Spinocerebellar ataxia (SCA) is a progressive, degenerative, genetic disease with multiple types. The signs and symptoms of an ataxia is one of a group of genetic disorders characterized by slowly progressive in coordination of gait and is often associated with poor coordination of hands, speech, and eye movements. With progression of the disease, patients lose postural stability and have gait dysfunction, difficulty in managing activities of daily living, and frequent falls. Although some motor dysfunctions may be alleviated with drug therapy, characteristics such as postural instability are less responsive to medication and require alternative approaches. The relevance of this study is timely; technology developments within the videogame sector are continually enhancing and pushing the boundaries to bring innovative and exciting modes of interaction to consumers. With this knowledge, maximizing the utility of such technologies into health services can offer methods for delivery of rehabilitation and training services.
In this paper, a motion-sensing based management system for smart context-awareness rehabilitation care was developed, consisting of a home-end motion-sensing rehabilitation exercise system and a remote care service platform. The home-end motion-sensing rehabilitation exercise system is equipped with various balance rehabilitation exercise models. The users’ whole-body image is captured using a motion-sensing camera and projected into virtual exercise scenarios. The users’ compliance is computed instantly through a motion analysis technology to provide exercise coaching instructions. The balance status of the users during exercise is subject to a realtime cross-analysis: the center of gravity (COG) trace is calculated using a depth image captured by a motionsensing camera; and the center of pressure (COP) trace is calculated using a pressure array sensor. In addition, the physiological information is incorporated to analyze physiological changes before, during, and after exercise. Through VoIP and streaming data integration technology, this system provides a real-time, one-to-multiple remote care service platform for exercise monitoring and interactive instructions.
2. System Framework
Figure 1 shows the motion-sensing based management system for smart context-awareness rehabilitation care, which is a home-end interactive motion-sensing rehabilitation exercise system that assists users in their balance rehabilitation exercises using several real-time sensors (motion-sensing camera, webcam, biomedical sensor, and pressure array sensor) through the wire/wireless connection (i.e., similar to the internet of things (IoT) model for physiological monitoring using motion-sensing rehabilitation). This system allows users to maintain their optimum exercise tolerance benchmark (that they reached in the hospital) within a certain range, and to enhance their compliance with the rehabilitation exercise and their balance function. Through physiological data that are detected automatically by a wireless physiological measuring device, this system au-to-computes the risks of patients encountering danger when exercising by themselves. Through a motion-sensing camera (e.g., Microsoft Kinect or ASUS Xtion PRO), the correctness of the users’ movements is automatically analyzed. Their balance status is cross-analyzed using a pressure array sensor and a motion-sensing camera. The remote care service platform integrates the VoIP, motion image analysis, exercise skeleton streaming, balance analysis, and physiological information convergence technologies to construct a personal health management platform server, enabling care managers to simultaneously and remotely supervise the actual conditions and physiological changes of several users during exercise. This system automatically alerts the telecare managers when the users’ physiological measurement or balance data are abnormal or when the system calculated risk is higher than usual. By using the data transmitted by the rehabilitation exercise system, the care managers can understand the problem and address it through VoIP or real-time video-conferencing to the patient’s home. In the following section, we introduce the home-end motion-sensing rehabilitation exercise system, the remote care service platform, and the clinical decision support system (CDSS) of the motionsensing based management system for smart contextawareness rehabilitation care.