Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet

Despite the functional impact of upper limb dysfunction in multiple sclerosis (MS), effects of intensive exercise programs and specifically robot-supported training have been rarely investigated in persons with advanced MS. To investigate the effects of additional robot-supported upper limb training in persons with MS compared to conventional treatment only. Seventeen persons with MS (pwMS) (median Expanded Disability Status Scale of 8, range 3.5–8.5) were included in a pilot RCT comparing the effects of additional robot-supported training to conventional treatment only. Additional training consisted of 3 weekly sessions of 30 min interacting with the HapticMaster robot within an individualised virtual learning environment (I-TRAVLE). Clinical measures at body function (Hand grip strength, Motricity Index, Fugl-Meyer) and activity (Action Research Arm test, Motor Activity Log) level were administered before and after an intervention period of 8 weeks. The intervention group were also evaluated on robot-mediated movement tasks in three dimensions, providing active range of motion, movement duration and speed and hand-path ratio as indication of movement efficiency in the spatial domain. Non-parametric statistics were applied. PwMS commented favourably on the robot-supported virtual learning environment and reported functional training effects in daily life. Movement tasks in three dimensions, measured with the robot, were performed in less time and for the transporting and reaching movement tasks more efficiently. There were however no significant changes for any clinical measure in neither intervention nor control group although observational analyses of the included cases indicated large improvements on the Fugl-Meyer in persons with more marked upper limb dysfunction. Robot-supported training lead to more efficient movement execution which was however, on group level, not reflected by significant changes on standard clinical tests. Persons with more marked upper limb dysfunction may benefit most from additional robot-supported training, but larger studies are needed. This trial is registered within the registry Clinical Trials GOV ( NCT02257606 ).

Mobile and tablet apps, ubiquitous and pervasive computing, wearable computing and domotics for health.

In Europe alone, on a yearly basis, millions of people need an appropriate exercise prescription to prevent the occurrence or progression of cardiovascular disease (CVD). A general exercise recommendation can be provided to these individuals (at least 150 min of moderate-intensity endurance exercise, spread over 3–5 days/week, complemented by dynamic moderate-intensity resistance exercise 2 days/week). However, recent evidence shows that this one size does not fit all and that individual adjustments should be made according to the patient’s underlying disease(s), risk profile, and individual needs, to maximize the clinical benefits of exercise. In this paper, we (i) argue that this general exercise prescription simply provided to all patients with CVD, or elevated risk for CVD, is insufficient for optimal CVD prevention, and (ii) show that clinicians and healthcare professionals perform heterogeneously when asked to adjust exercise characteristics (e.g. intensity, volume, and type) according to the patient’s condition, thereby leading to suboptimal CVD risk factor control. Since exercise training is a class 1A intervention in the primary and secondary prevention of CVD, the awareness of the need to improve exercise prescription has to be raised among clinicians and healthcare professionals if optimized prevention of CVD is ambitioned.

Background: 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.