Strategies for Long-Term Maintenance of Physical Activity Among Older Adults: A Qualitative Study From India.

Long-term physical activity (PA) maintenance is challenging for older adults. Equipping older adults with strategies to support long-term PA maintenance can be an effective way to tackle this problem. Moreover, there is a lack of studies regarding long-term PA maintenance among older adults from non-Western settings. This qualitative research is one of the first studies conducted in an Indian context that explores the strategies developed and utilized by older adults who have successfully maintained their PA for the long term (>1 year) in their home settings. In-depth semistructured interviews were conducted with 19 older adults, and data were analyzed using an inductive reflexive thematic analysis approach. This article reports five strategies of PA maintenance, together comprising 13 substrategies. This study highlights the importance of using strategies to support the long-term maintenance of PA among older adults in India. However, these strategies would also be useful in other sociocultural contexts.

Learning an EMG Controlled Game: Task-Specific Adaptations and Transfer.

Video games that aim to improve myoelectric control (myogames) are gaining popularity and are often part of the rehabilitation process following an upper limb amputation. However, direct evidence for their effect on prosthetic skill is limited. This study aimed to determine whether and how myogaming improves EMG control and whether performance improvements transfer to a prosthesis-simulator task. Able-bodied right-handed participants (N = 28) were randomly assigned to 1 of 2 groups. The intervention group was trained to control a video game (Breakout-EMG) using the myosignals of wrist flexors and extensors. Controls played a regular Mario computer game. Both groups trained 20 minutes a day for 4 consecutive days. Before and after training, two tests were conducted: one level of the Breakout-EMG game, and grasping objects with a prosthesis-simulator. Results showed a larger increase of in-game accuracy for the Breakout-EMG group than for controls. The Breakout-EMG group moreover showed increased adaptation of the EMG signal to the game. No differences were found in using a prosthesis-simulator. This study demonstrated that myogames lead to task-specific myocontrol skills. Transfer to a prosthesis task is therefore far from easy. We discuss several implications for future myogame designs.

iLift: A health behavior change support system for lifting and transfer techniques to prevent lower-back injuries in healthcare.

OBJECTIVE: Lower back problems are a common cause of sick leave of employees in Dutch care homes and hospitals. In the Netherlands over 40% of reported sick leave is due to back problems, mainly caused by carrying out heavy work. The goal of the iLift project was to develop a game for nursing personnel to train them in lifting and transfer techniques. The main focus was not on testing for the effectiveness of the game itself, but rather on the design of the game as an autogenous trigger and its place in a behavioral change support system. In this article, the design and development of such a health behavior change support system is addressed, describing cycles of design and evaluation. METHODS: (a) To define the problem space, use context and user context, focus group interviews were conducted with Occupational Therapists (n=4), Nurses (n=10) and Caregivers (n=12) and a thematic analysis was performed. We interviewed experts (n=5) on the subject of lifting and transferring techniques. (b) A design science research approach resulted in a playable prototype. An expert panel conducted analysis of video-recorded playing activities. (c) Field experiment: We performed a dynamic analysis in order to investigate the feasibility of the prototype through biometric data from player sessions (n=620) by healthcare professionals (n=37). RESULTS: (a) Occupational Therapists, Nurses and Caregivers did not recognise a lack of knowledge with training in lifting and transferring techniques. All groups considered their workload, time pressure and a culturally determined habit to place the patient's well being above their own as the main reason not to apply appropriate lifting and transferring techniques. This led to a shift in focus from a serious game teaching lifting and transferring techniques to a health behavior change support system containing a game with the intention to influence behavior. (b) Building and testing (subcomponents of) the prototype resulted in design choices regarding players perspective, auditory and visual feedback, overall playability and perceived immersiveness. This design process also addressed the behavior shaping capacities of the game and its place within the health behavior change support system. An expert panel on lifting and transferring techniques validated the provoked in-game activities as being authentic. (c) Regression analysis showed an increase of the game score and dashboard score when more sessions were played, indicating an in-game training effect. A post-hoc test revealed that from an average of 10 playing sessions or more, the dashboard score and the game score align, which indicates behavioral change towards executing appropriate static lifting and transferring techniques. CONCLUSIONS: Data gathered in the final field test shows an in-game training effect, causing players to exhibit correct techniques for static lifting and transferring techniques but also revealed the necessity for future social system development and especially regarding intervention acceptance. Social system factors showed a strong impact on the games persuasive capacities and its autogenous intent.

Task-Oriented Gaming for Transfer to Prosthesis Use.

The aim of this study is to establish the effect of task-oriented video gaming on using a myoelectric prosthesis in a basic activity of daily life (ADL). Forty-one able-bodied right-handed participants were randomly assigned to one of four groups. In three of these groups the participants trained to control a video game using the myosignals of the flexors and extensors of the wrist: in the Adaptive Catching group participants needed to catch falling objects by opening and closing a grabber and received ADL-relevant feedback during performance. The Free Catching group used the same game, but without augmented feedback. The Interceptive Catching group trained a game where the goal was to intercept a falling object by moving a grabber to the left and right. They received no additional feedback. The control group played a regular Mario computer game. All groups trained 20 minutes a day for four consecutive days. Two tests were conducted before and after training: one level of the training game was performed, and participants grasped objects with a prosthesis simulator. Results showed all groups improved their game performance over controls. In the prosthesis-simulator task, after training the Adaptive Catching group outperformed the other groups in their ability to adjust the hand aperture to the size of the objects and the degree of compression of compressible objects. This study is the first to demonstrate transfer effects from a serious game to a myoelectric prosthesis task. The specificity of the learning effects suggests that research into serious gaming will benefit from placing ADL-specific constraints on game development.

Sensor networks in the low lands.

This paper provides an overview of scientific and industrial developments of the last decade in the area of sensor networks in The Netherlands (Low Lands). The goal is to highlight areas in which the Netherlands has made most contributions and is currently a dominant player in the field of sensor networks. On the one hand, motivations, addressed topics, and initiatives taken in this period are presented, while on the other hand, special emphasis is given to identifying current and future trends and formulating a vision for the coming five to ten years. The presented overview and trend analysis clearly show that Dutch research and industrial efforts, in line with recent worldwide developments in the field of sensor technology, present a clear shift from sensor node platforms, operating systems, communication, networking, and data management aspects of the sensor networks to reasoning/cognition, control, and actuation.