Use of a technology-based system to motivate older adults in performing physical activity: a feasibility study.

BACKGROUND: Maintaining or initiating regular physical activity (PA) is important for successful aging. Technology-based systems may support and stimulate older adults to initiate and persevere in performing PA. The aim of the current study was to assess to which extent a customised Kinect system is 1) a credible tool to increase PA in older adults, 2) motivating to perform PA by older adults, and 3) easy to be used in older adults. METHODS: A mixed-method cross-sectional feasibility study was performed in 5 aged care facilities in Flanders, Belgium. Aged participants were asked to perform a 20-30 min test with the intelligent Activity-based Client-centred Training (i-ACT) system. After the test, the 'Credibility and Expectancy Questionnaire' (CEQ), the 'Intrinsic Motivation Inventory'(IMI), the System Usability Scale (SUS), and semi-structured interviews were conducted in the older adults. Feedback was gathered using the thinking aloud method in both aged participants and healthcare professionals. RESULTS: A total of 48 older adults (20 males and 28 females, mean age = 81.19 (SD = 8.10)), were included. The scores pertaining to system credibility and expectancy, system usability, and motivation towards use were moderate to good. Participants reported that they liked using the i-ACT system, but that the context could be more attractive by adding more visualisations. Twelve professionals stated that they observed involvement in older adults but think that i-ACT is better used in day care centres. CONCLUSIONS: This study indicates that i-ACT is a usable and motivational system to engage older adults to perform PA and therefore supports successful aging. Future research is necessary to investigate the efficacy of i-ACT to perform PA and the transfer to regain and/or maintain engagement in ADLs that older adults find meaningful and purposeful at an older age. Also, further development of i-ACT is advisable to adapt the i-ACT system towards implementation at the home of older adults. TRIAL REGISTRATION: ClinicalTrial.gov ID NCT04489563 , 23 July 2020 - Retrospectively registered.

Design, Development, and Testing of an App for Dual-Task Assessment and Training Regarding Cognitive-Motor Interference (CMI-APP) in People With Multiple Sclerosis: Multicenter Pilot Study.

BACKGROUND: Dual tasking constitutes a large portion of most activities of daily living; in real-life situations, people need to not only maintain balance and mobility skills, but also perform other cognitive or motor tasks at the same time. Interest toward dual-task training (DTT) is increasing as traditional interventions may not prepare patients to adequately face the challenges of most activities of daily living. These usually involve simultaneous cognitive and motor tasks, and they often show a decline in performance. Cognitive-motor interference (CMI) has been investigated in different neurological populations, but limited evidence is present for people with multiple sclerosis (MS). The use of computerized tools is mandatory to allow the application of more standardized assessment and rehabilitation intervention protocols and easier implementation of multicenter and multilanguage studies. OBJECTIVE: To describe the design and development of CMI-APP, an adaptive and interactive technology tablet-based app, and to present the preliminary results of a multicenter pilot study involving people with MS performed in several European centers for evaluating the feasibility of and adherence to a rehabilitation program based on CMI-APP. METHODS: CMI-APP includes user-friendly interfaces for personal data input and management, assessment of CMI, and DTT. A dedicated team developed CMI-APP for Android tablets above API level 14 (version 4.0), using C# as the programming language and Unity and Visual Studio as development tools. Three cognitive assessment tests for working memory, information processing speed, and sustained attention and four motor assessment tests for walking at different difficulty levels were implemented. Dual cognitive-motor tasks were performed by combining single cognitive and motor tasks. CMI-APP implements exercises for DTT involving the following 12 cognitive functions: sustained attention, text comprehension, verbal fluency, auditory discrimination, visual discrimination, working memory, information processing speed, auditory memory, visual memory, verbal analog reasoning, visual analog reasoning, and visual spatial planning, which can be performed during walking or stepping on the spot. Fifteen people with MS (mean age 52.6, SD 8.6 years; mean disease duration 9.4, SD 8.4 years; mean Expanded Disability Status Scale score 3.6, SD 1.1) underwent DTT (20 sessions). Adherence to the rehabilitation program was evaluated according to the percentage of performed sessions, perceived exertion during the training (Borg 15-point Ratings of Perceived Exertion [RPE] Scale), and subjective experience of the training (Intrinsic Motivation Inventory [IMI]). RESULTS: The adherence rate was 91%. DTT was perceived as "somewhat difficult" (mean RPE Scale score 12.6, SD 1.9). IMI revealed that participants enjoyed the training and felt that it was valuable and, to some extent, important, without feelings of pressure. They felt competent, although they did not always feel they could choose the exercises, probably because the therapist chose the exercises and many exercises had few difficulty levels. CONCLUSIONS: CMI-APP is safe, highly usable, motivating, and well accepted for DTT by people with MS. The findings are fundamental for the preparation of future large-sample studies examining CMI and the effectiveness of DTT interventions with CMI-APP in people with MS.

Developing an intelligent activity-based client-centred training system with a user-centred approach.

BACKGROUND: In neurorehabilitation, clinicians and managers are searching for new client-centred task-oriented applications which can be administered without extra costs and effort of therapists, and increase the client's motivation. OBJECTIVE: To develop and evaluate a prototype of an intelligent activity-based client-centred training (i-ACT) system based on Microsoft Kinect®. METHODS: Within an iterative user centred process, the i-ACT prototype was developed and necessary features were established for use in neurological settings. After the test trial with a high fidelity prototype, the value, usefulness, and credibility were evaluated. RESULTS: Seven therapists participated in focus groups and 54 persons with neurological problems participated in test trials. A prototype was established based on the user's experience. Results show that clients and therapists acknowledge the value and usefulness (clients 5.71/7; therapists 4.86/7), and credibility (clients 21.00/27; therapists 14.50/27) of i-ACT. CONCLUSIONS: Therapists want to be able to record an endless range of movements and activities which enables individualised exercise programs for persons with disabilities. For therapists it is important that the system provides feedback about the quality of movement and not only results. In future work, clinical trials will be performed towards feasibility and effectiveness of i-ACT in neurorehabilitation and other rehabilitation domains.

Motion detection supported exercise therapy in musculoskeletal disorders: a systematic review.

INTRODUCTION: Musculoskeletal disorders (MSDs) are a burden on the healthcare system. Exercise therapy is an important part of MSD rehabilitation. Motion detection systems are developed to support exercise therapy settings. This systematic review aimed: 1) at investigating which types of motion detection systems have been used as a technological support for exercise therapy; 2) at investigating the characteristics of motion detection supported exercise therapy in relation to its clinical indications; and 3) at evaluating the effectiveness of motion detection supported exercise therapy, in MSD rehabilitation. EVIDENCE AQCUISITION: A systematic literature search for RCTs was performed in six databases (PubMed, CINAHL, EMBASE, ACM, Cochrane, and IEEE). Studies eligible for inclusion had to evaluate exercise therapy for persons with MSDs, provide a motion detection system capable of as well measuring active movement of the participant during exercise therapy as evaluating the movement in order to provide qualitative feedback, and should present at least one measure of the following ICF function (pain, muscle strength, mobility), activity (disease-related functional disability, balance) or participation (quality of life) level. Two reviewers independently screened articles, appraised study quality, extracted data, and evaluated effectiveness of selected outcome measures. This review was registered in the International prospective register of systematic reviews (Prospero) under registration number CRD42016035273. EVIDENCE SYNTHESIS: Nine RCTs (N.=432 participants) were included. Eight different motion detection technologies were used such as an accelerometer, gyroscope, magnetometer etc. All systems provided visual feedback. Knee disorders were evaluated most frequently, followed by low back pain and shoulder disorders. Therapy consisted of mobility, balance or proprioception exercises. Main outcomes were pain, disability, mobility and muscle strength. Motion detection supported exercise therapy showed similar or enhanced results on all outcomes compared to conventional exercise therapy. However, a limitation of this study was the low methodological quality of the studies. CONCLUSIONS: To date, a variety of motion detection systems have been developed to support the rehabilitation of MSDs. Results show similar effectiveness of motion detection supported exercise therapy compared to conventional exercise therapy. More research is needed to provide insight in the added value of motion detection systems in musculoskeletal rehabilitation.

Markerless motion capture systems as training device in neurological rehabilitation: a systematic review of their use, application, target population and efficacy.

BACKGROUND: Client-centred task-oriented training is important in neurological rehabilitation but is time consuming and costly in clinical practice. The use of technology, especially motion capture systems (MCS) which are low cost and easy to apply in clinical practice, may be used to support this kind of training, but knowledge and evidence of their use for training is scarce. The present review aims to investigate 1) which motion capture systems are used as training devices in neurological rehabilitation, 2) how they are applied, 3) in which target population, 4) what the content of the training and 5) efficacy of training with MCS is. METHODS: A computerised systematic literature review was conducted in four databases (PubMed, Cinahl, Cochrane Database and IEEE). The following MeSH terms and key words were used: Motion, Movement, Detection, Capture, Kinect, Rehabilitation, Nervous System Diseases, Multiple Sclerosis, Stroke, Spinal Cord, Parkinson Disease, Cerebral Palsy and Traumatic Brain Injury. The Van Tulder's Quality assessment was used to score the methodological quality of the selected studies. The descriptive analysis is reported by MCS, target population, training parameters and training efficacy. RESULTS: Eighteen studies were selected (mean Van Tulder score = 8.06 ± 3.67). Based on methodological quality, six studies were selected for analysis of training efficacy. Most commonly used MCS was Microsoft Kinect, training was mostly conducted in upper limb stroke rehabilitation. Training programs varied in intensity, frequency and content. None of the studies reported an individualised training program based on client-centred approach. CONCLUSION: Motion capture systems are training devices with potential in neurological rehabilitation to increase the motivation during training and may assist improvement on one or more International Classification of Functioning, Disability and Health (ICF) levels. Although client-centred task-oriented training is important in neurological rehabilitation, the client-centred approach was not included. Future technological developments should take up the challenge to combine MCS with the principles of a client-centred task-oriented approach and prove efficacy using randomised controlled trials with long-term follow-up. TRIAL REGISTRATION: Prospero registration number 42016035582 .