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Gait and dynamic balance are two main goals in neurorehabilitation that mHealth systems could address. To analyze the impact of using mHealth systems on gait and dynamic balance outcomes in subjects with neurological disorders. Randomized controlled trials (RCT) published in PubMed, Web of Science, Scopus, and PEDro databases were searched up to April 2023. Studies including adults with neurological disorders, analyzing the effectiveness of mHealth systems on gait and dynamic balance compared with conventional therapy and/or not intervention, were included. The PEDro scale and the Cochrane Collaboration's 2.0 tool were used for the methodological quality and risk of bias assessment. The Review Manager 5.4 software was used to obtain meta-analyses. 13 RCT were included in the systematic review and 11 in the meta-analyses, involving 528 subjects. A total of 21 mobile applications were identified for gait and balance training, and to enhance physical activity behaviors. There were significant differences in gait parameters, speed by 0.10 s/m (95% confidence interval (CI)=0.07,0.13;p<0.001), cadence by 8.01 steps/min (95%CI=3.30,12.72;p<0.001), affected step length by 8.89 cm (95%CI=4.88,12.90;p<0.001), non-affected step length by 8.08 cm (5%CI=2.64,13.51;p=0.004), and in dynamic balance, Timed Up and Go by -7.15 s (95%CI=-9.30,-4.99;p<0.001), and mobility subscale of Posture Assessment Scale for Stroke by 1.71 points (95%CI=1.38,2.04;p<0.001). Our findings suggested the use of mHealth systems for improving gait in subjects with neurological disorders, but controversial results on dynamics balance recovery were obtained. However, the quality of evidence is insufficient to strongly recommend them, so further research is needed., (© 2023. The Author(s).)

Background: Chronic pain (CP) is 1 of the leading causes of disability worldwide and represents a significant burden on individual, social, and economic aspects. Potential tools, such as mobile health (mHealth) systems, are emerging for the self-management of patients with CP., Objective: A systematic review was conducted to analyze the effects of mHealth interventions on CP management, based on pain intensity, quality of life (QoL), and functional disability assessment, compared to conventional treatment or nonintervention., Methods: PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines were followed to conduct a systematic review of randomized controlled trials (RCTs) published in PubMed, Web of Science, Scopus, and Physiotherapy Evidence Database (PEDro) databases from February to March 2022. No filters were used. The eligibility criteria were RCTs of adults (≥18 years old) with CP, intervened with mHealth systems based on mobile apps for monitoring pain and health-related outcomes, for pain and behavioral self-management, and for performing therapeutic approaches, compared to conventional treatments (physical, occupational, and psychological therapies; usual medical care; and education) or nonintervention, reporting pain intensity, QoL, and functional disability. The methodological quality and risk of bias (RoB) were assessed using the Checklist for Measuring Quality, the Oxford Centre for Evidence-Based Medicine Levels of Evidence, and the Cochrane RoB 2.0 tool., Results: In total, 22 RCTs, involving 2641 patients with different CP conditions listed in the International Classification of Diseases 11th Revision (ICD-11), including chronic low back pain (CLBP), chronic musculoskeletal pain (CMSP), chronic neck pain (CNP), unspecified CP, chronic pelvic pain (CPP), fibromyalgia (FM), interstitial cystitis/bladder pain syndrome (IC/BPS), irritable bowel syndrome (IBS), and osteoarthritis (OA). A total of 23 mHealth systems were used to conduct a variety of CP self-management strategies, among which monitoring pain and symptoms and home-based exercise programs were the most used. Beneficial effects of the use of mHealth systems in reducing pain intensity (CNP, FM, IC/BPS, and OA), QoL (CLBP, CNP, IBS, and OA), and functional disability (CLBP, CMSP, CNP, and OA) were found. Most of the included studies (18/22, 82%) reported medium methodological quality and were considered as highly recommendable; in addition, 7/22 (32%) studies had a low RoB, 10/22 (45%) had some concerns, and 5/22 (23%) had a high RoB., Conclusions: The use of mHealth systems indicated positive effects for pain intensity in CNP, FM, IC/BPS, and OA; for QoL in CLBP, CNP, IBS, and OA; and for functional disability in CLBP, CMSP, CNP, and OA. Thus, mHealth seems to be an alternative to improving pain-related outcomes and QoL and could be part of multimodal strategies for CP self-management. High-quality studies are needed to merge the evidence and recommendations of the use of mHealth systems for CP management., Trial Registration: PROSPERO International Prospective Register of Systematic Reviews CRD42022315808; https://www.crd.york.ac.uk/prospero/display&#95;record.php?RecordID=315808., (©Marta Moreno-Ligero, Jose A Moral-Munoz, Alejandro Salazar, Inmaculada Failde. Originally published in JMIR mHealth and uHealth (https://mhealth.jmir.org), 02.02.2023.)

Tele-(remote) rehabilitation is attracting increased attention from society, including the research community and commercial marketplace with an estimated global market value of $160 billion. Meanwhile, mobile device-based healthcare ("mHealth") has appeared as a revolutionary approach to tele-rehabilitation practice. This paper presents a systematic review of the literature on smartphone-based systems designed for remote facilitation of physical rehabilitation. A total of 74 documents from Web of Science search results were reviewed. Systems were classified based on target medical conditions, and a taxonomy of technology was created along with identification of monitored activities. Beyond monitoring, some systems also provide patient-caregiver communication and progress management functions. The review identifies major research interests in stroke, cardiac disease, balance impairment and joint/limb rehabilitation; however, there is a lack of attention to other diseases. There are also few systems that have computerized existing clinical tests. On the basis of the review, design recommendations are formulated to encourage implementation of advanced functionalities, usability considerations, and system validation based on clinical evidence. Results of this study may help researchers and companies to design functions and interactions of smartphone-based rehabilitation systems or to select technology.

The development of innovative solutions that allow the aging population to remain healthier and independent longer is essential to alleviate the burden that this increasing segment of the population supposes for the long term sustainability of the public health systems. It has been claimed that promoting physical activity could prevent functional decline. However, given the vulnerability of this population, the activity prescription requires to be tailored to the individual's physical condition. We propose mobile Senior Fitness Test (m-SFT), a novel m-health system, that allows the health practitioner to determine the elderly physical condition by implementing a smartphone-based version of the senior fitness test (SFT). The technical reliability of m-SFT has been tested by carrying out a comparative study in seven volunteers (53-61 years) between the original SFT and the proposed m-health system obtaining high agreement (intra-class correlation coefficient (ICC) between 0.93 and 0.99). The system usability has been evaluated by 34 independent health experts (mean = 36.64 years; standard deviation = 6.26 years) by means of the System Usability Scale (SUS) obtaining an average SUS score of 84.4 out of 100. Both results point out that m-SFT is a reliable and easy to use m-health system for the evaluation of the elderly physical condition, also useful in intervention programs to follow-up the patient's evolution.

Objective: Stroke is the leading cause of physical disability in the adult population. Technology at the service of medicine provides new solutions for the assessment, treatment, and monitoring of subjects with neurological disorders. Therefore, the aim of this study was to review the use of commercial mobile applications in the therapeutic approach of subjects who have suffered a stroke, as well as to analyze if there is scientific evidence on their use., Methods: A search of specific apps for the therapeutic approach to stroke, as well as its possible clinical aftereffects, in the main applications repositories was made: "Google Play" and "App Store". Besides, the possible scientific evidence for each app obtained was analyzed using the following databases: Web of Science, Pubmed, ScienceDirect, Scopus and Google Scholar., Results: A total of 45 apps were obtained meeting the criteria established in the study. These were subdivided into different categories: assessment tools (13), therapeutic exercise program (8) perception of laterality and body scheme (7), management of secondary disorders (7), mobility, dexterity and manual coordination (5) and postural correction and ergonomics (5). From the 45 apps obtained, only 10 of them had been used in scientific studies., Conclusions: There is a wide variety of commercial mobile applications of great utility and low cost, applicable in the assessment and treatment of subjects who have suffered a stroke, there is even scientific evidence, although limited, about the validity of such apps.

Low back pain is the most prevalent musculoskeletal condition. This disorder constitutes one of the most common causes of disability worldwide, and as a result, it has a severe socioeconomic impact. Endurance tests are normally considered in low back pain rehabilitation practice to assess the muscle status. However, traditional procedures to evaluate these tests suffer from practical limitations, which potentially lead to inaccurate diagnoses. The use of digital technologies is considered here to facilitate the task of the expert and to increase the reliability and interpretability of the endurance tests. This work presents mDurance, a novel mobile health system aimed at supporting specialists in the functional assessment of trunk endurance by using wearable and mobile devices. The system employs a wearable inertial sensor to track the patient trunk posture, while portable electromyography sensors are used to seamlessly measure the electrical activity produced by the trunk muscles. The information registered by the sensors is processed and managed by a mobile application that facilitates the expert's normal routine, while reducing the impact of human errors and expediting the analysis of the test results. In order to show the potential of the mDurance system, a case study has been conducted. The results of this study prove the reliability of mDurance and further demonstrate that practitioners are certainly interested in the regular use of a system of this nature.

Aim: To evaluate the effectiveness of PainReApp, an mHealth system, based on physical exercise recommendations for patients with chronic pain (low back pain, fibromyalgia and diabetic neuropathic pain) based on pain intensity, quality of life, anxiety and/or depression, and sleep quality. Design: Single‐blinded randomized controlled trial. Methods: One hundred patients from three different chronic conditions (low back pain, fibromyalgia and neuropathic diabetic pain) will be recruited and randomized into two groups to receive the intervention with a physical activity program guided by the PainReApp system (experimental group) or with the program information in paper format (control group). All patients will attend a first face‐to‐face session in which the smartphone application usage (experimental group) and exercise execution will be explained (both groups). Data will be collected at baseline, 4, 12 and 24 weeks. Nevertheless, the users of the application will have a daily registry of the exercise performed and the self‐perceived difficulty. The primary outcomes of the trial will be the intensity of pain and quality of life. Anxiety and/or depression and sleep quality will be also assessed to evaluate the influence of the physical activity at multiple levels. Discussion: Physical exercise is becoming one of the leading evidence‐based interventions to treat chronic pain. It needs to be adapted to the necessities of each pain condition. One of the major problems is the low adherence to the proposed program. New strategies that empower the patients, such as the m‐Health, are reliable and useful tools to ease this end. Impact: To the best of our knowledge, this is the first long‐term randomized controlled trial researching the impact of an m‐health system on chronic pain from different origin. The intervention is based on international physical exercise recommendations and can be performed without specific material, allowing the home‐based practice. Trial registration: Australian and New Zealand Clinical Trials Registry (ACTRN12621000783820). [ABSTRACT FROM AUTHOR]

Body balance disorders are related to different injuries that contribute to a wide range of healthcare issues. The social and financial costs of these conditions are high. Therefore, quick and reliable body balance assessment can contribute to the prevention of injuries, as well as enhancement of clinical rehabilitation. Moreover, the use of smartphone applications is increasing rapidly since they incorporate different hardware components that allow for body balance assessment. The present study aims to show an analysis of the current applications available on Google Play StoreTM and iTunes App StoreTM to measure this physical condition, using the Mobile Application Rating Scale (MARS). Three iOS and two Android applications met the inclusion criteria. Three applications have scientific support, Balance test YMED, Balance Test by Slani, and Sway. Furthermore, according to MARS, the main scores for each evaluated domain were: Engagement (2.04), Functionality (3.8), Esthetics (3.53), and Information (3.80). The reviewed applications targeted to assess body balance obtained good mean scores. Sway is the app with highest scores in each MARS domain, followed by iBalance Fitness and Gyrobalance. [ABSTRACT FROM AUTHOR]