The design and usability evaluation of a monitoring and feedback system for stroke survivors

The impact of stroke on the world is significant, with high disability rates among survivors and rising costs in healthcare. Therefore, new healthcare strategies and technological solutions should be found in stroke care. Is it possible to reduce healthcare costs, and at the same time make treatment more efficient? It has already been shown that specialized stroke care improves health and economic outcomes. Furthermore, Monitoring patients in their homes, using telemedicine techniques, can lead to better health care at lower costs. Both imply increased demand of new healthcare strategies and technological solutions. If monitoring stroke survivors in their home environment is the solution for a reduction in healthcare cost and a more efficient treatment plan, what information is missing in order to implement such technical solutions in healthcare? Stroke survivors are trained to recover adequate control over their movements with the objective to optimize their daily-life functional performance. While, the main objective of the rehabilitation program is to maximize the functional performance at home, the actual performance of patients in their home environment is unknown. Therefore, daily-life monitoring of the quality of movement during functional activities of stroke survivors in their physical interaction with the environment is essential for optimal guidance of rehabilitation therapy. There are several challenges in performing a quantitative and qualitative analysis of daily-life performance using telemedicine technology, compared to clinically assess motor capacity using standardized clinical tests. This includes: the development of new metrics for quantifying movement during daily-life, the absence of context when measuring movements without any visual reference, which is available in clinic but not available in a daily-life setting and finally, the presentation of large amount of movement data to care-professionals. Therefore, there is a need to investigate into how stroke survivors can be monitored during daily-life, which telemonitoring technology to include and what to present to care-professionals. This thesis, supported by the FP7 project INTERACTION, addresses two main objectives: 1) to develop and evaluate a tele-supervision system and intelligent on-body feedback technology for monitoring and coaching stroke survivors in a home environment and 2) develop and evaluate new quality of movement metrics in stroke survivors. The research presented in this thesis has contributed to both fundamental and applied areas of science and also has an important (potential) societal impact regarding diagnostics and treatment of (stroke) survivors by enabling quantitative monitoring during daily-life activities. A literature survey on telemedicine systems presented new insights which can help researchers in optimizing their usability strategies during system development and predicting future trends in usability evaluation strategies. In a multidisciplinary team, with particular focus on the telemonitoring aspects, a full-body inertial sensing system, unobtrusive to wear by stroke survivors during daily-life was realised. This system is named: INTERACTION. This system was used to monitor stroke survivors at home to gain new insights into the performance of these patients during daily-life activities. Clinically relevant Quality of Movement (QoM) metrics were developed, implemented and evaluated, enabling new insights into the differences between in-clinic and outpatient measurements of stroke survivors over longer periods of time. This in turn might assist care-professionals in understanding what is happening with stroke survivors after discharge from the hospital to their homes. In addition to the INTERACTION system, a reduced sensor system (the “Arm Usage Coach”), capable of monitoring and coaching stroke survivors by giving feedback based on arm movement activity, was designed, implemented and evaluated. This, in turn might engage patients in using their impaired arm more often during daily-life activities. It was found that stroke survivors prefer vibrotactile feedback as a feedback method, which sets the foundation for other researchers in developing assistive technological devices for stroke survivors. Insights on the opinions given by care-professionals in using inertial motion capture as an assistive technology, including working with QoM metrics as opposed to traditional clinical assessments, was given. Developers in assistive devices for healthcare still face the problem that many care-professionals slowly adapt new technology into their daily-practices. The findings presented in this thesis might help other developers in understanding what is important, in our case related to an inertial motion capture system and associated metrics, and take new approaches in designing and introducing assistive devices into daily practices. For taking the research presented in this thesis further, it would be interesting to investigate into the optimisation of INTERACTION and the motivational aspects of the patient for performing in clinic and at home. If the INTERACTION system can be less obtrusive to wear by patients and implemented on a larger scale, we can gain more knowledge from a wider variety of stroke patients. Big data approaches can be used to analyse the data, see trends over time and gain more insights into the usage of the system. If so, it might result in a change in therapy of stroke survivors and outpatient, ambulant monitoring and coaching will increase.