Telerehabilitation requires accurate joint range of motion (ROM) measurement methods. The aim of this study was to evaluate the reliability and validity of a computer vision (CV)-based markerless human pose estimation (HPE) application measuring active hip and knee ROMs. For this study, the joint ROM of 30 healthy young adults (10 females, 20 males) aged 20-33 years (mean: 22.9 years) was measured, and test-retests were assessed for reliability. For validity evaluation, the CV-based markerless HPE application used in this study was compared with an identical reference picture frame. The intraclass correlation coefficient (ICC) for the CV-based markerless HPE application was 0.93 for active hip inner rotation, 0.83 for outer rotation, 0.82 for flexion, 0.82 for extension, and 0.74 for knee flexion. Correlations (r) of the two measurement methods were 0.99 for hip-active inner rotation, 0.98 for outer rotation, 0.87 for flexion, 0.85 for extension, and 0.90 for knee flexion. This study highlights the potential of a CV-based markerless HPE application as a reliable and valid tool for measuring hip and knee joint ROM. It could offer an accessible solution for telerehabilitation, enabling ROM monitoring.

The use of humanoid robots, in the field of rehabilitation, has increased over the last years as the technology has become more sophisticated. The aim of this paper is to explore the possibility of using humanoid robots in rehabilitation for children and youth with cerebral palsy (CP). A total of 9 papers were found with inclusion criteria of children with CP, rehabilitation and humanoid robots. In these 9 papers there were 40 children with reported CP diagnosis, age range from 2.11 to 18 years. We found that humanoid robots tested in real rehabilitation scenarios were NAO, ZORA, MARKO and URSUS. These were mostly used in simple rehabilitation interventions as motivators in different exercises for joint mobility or therapeutic exercises in legs or arms. Our findings show that humanoid robots need to be toughly tested following a complete standard process for planning, experimenting and reporting before being used in rehabilitation. In addition, our analysis shows that QTrobot has a huge potential for the rehabilitation of CP children.

ObjectiveTo investigate physiotherapists' views on suitability, usability and factors affecting the use of remote physiotherapy in Finland.DesignA cross-sectional, web-based questionnaire study.SubjectsMembers of the Finnish Association of Physiotherapists and a private physiotherapy organisation.MethodsThe questionnaire included questions on remote physiotherapy & PRIME;s suitability (0 = not suitable at all to 10 = fully suitable) for different physiotherapy tasks (consultation, guidance and counselling, exercise, assessment and corrective act at the workplace), a reason to implement remote physiotherapy, how often remote physiotherapy is used at different stages of the physiotherapy process and factors affecting the use of remote physiotherapy.Results The response rate was 9.9% (N=662/6525; 76.1% female). The mean suitability 'score' for remote physiotherapy differed from 7.6 (consultation, guidance and counselling) to 3.8 (corrective act at a workplace). Physiotherapists with at least one year experience of working with remote physiotherapy reported that it is better suited to consultation, guidance and counselling, exercise and assessment (p-values <.05) than did those with less experience. Of the responders (physiotherapists), 72.5% used conventional physiotherapy, 7.2% used remote physiotherapy and 20.2% used a combination of the two as primary work method.ConclusionPhysiotherapists stated that remote physiotherapy suits especially for consultation, guidance and counselling, but it is still minimally used as primary work method in different stages of the physiotherapy process.

Background The ongoing COVID-19 pandemic has required social, health, and rehabilitation organizations to implement remote physiotherapy (RP) as a part of physiotherapists’ daily practice. RP may improve access to physiotherapy as it delivers physiotherapy services to rehabilitees through information and communications technology. Even if RP has already been introduced in this century, physiotherapists’ opinion, amount of use, and form in daily practice have not been studied extensively. Objective This study aims to investigate physiotherapists’ opinions of the current state of RP in Finland. Methods A quantitative, cross-sectional, web-based questionnaire was sent to working-aged members of the Finnish Association of Physiotherapists (n=5905) in March 2021 and to physiotherapists in a private physiotherapy organization (n=620) in May 2021. The questionnaire included questions on the suitability of RP in different diseases and the current state and implementation of RP in work among physiotherapists. Results Of the 6525 physiotherapists, a total of 9.9% (n=662; n=504, 76.1% female; mean age 46.1, SD 12 years) answered the questionnaire. The mean suitability “score” (0=not suitable at all to 10=fully suitable) of RP in different disease groups varied from 3.3 (neurological diseases) to 6.1 (lung diseases). Between early 2020 (ie, just before the COVID-19 pandemic) and spring 2021, the proportion of physiotherapists who used RP increased from 33.8% (21/62) to 75.4% (46/61; P<.001) in the public sector and from 19.7% (42/213) to 76.6% (163/213; P<.001) in the private sector. However, only 11.7% (32/274) of physiotherapists reported that they spent >20% of their practice time for RP in 2021. The real-time method was the most common RP method in both groups (public sector 46/66, 69.7% vs private sector 157/219, 71.7%; P=.47). The three most commonly used technical equipments were computers/tablets (229/290, 79%), smartphones (149/290, 51.4%), and phones (voice call 51/290, 17.6%). The proportion of physiotherapists who used computers/tablets in RP was higher in the private sector than in the public sector (183/221, 82.8% vs 46/68, 67.6%; P=.01). In contrast, a higher proportion of physiotherapists in the public sector than in the private sector used phones (18/68, 26.5% vs 33/221, 14.9%; P=.04). Conclusions During the COVID-19 pandemic, physiotherapists increased their use of RP in their everyday practice, although practice time in RP was still low. When planning RP for rehabilitees, it should be considered that the suitability of RP in different diseases seems to vary in the opinion of physiotherapists. Furthermore, our results brought up important new information for developing social, health, and rehabilitation education for information and communications technologies.

BACKGROUND:Several factors, including the aging population and the recent corona pandemic, have increased the need for cost effective, easy-to-use and reliable telerehabilitation services. Computer vision-based marker-less human pose estimation is a promising variant of telerehabilitation and is currently an intensive research topic. It has attracted significant interest for detailed motion analysis, as it does not need arrangement of external fiducials while capturing motion data from images. This is promising for rehabilitation applications, as they enable analysis and supervision of clients' exercises and reduce clients' need for visiting physiotherapists in person. However, development of a marker-less motion analysis system with precise accuracy for joint identification, joint angle measurements and advanced motion analysis is an open challenge.OBJECTIVES:The main objective of this paper is to provide a critical overview of recent computer vision-based marker-less human pose estimation systems and their applicability for rehabilitation application. An overview of some existing marker-less rehabilitation applications is also provided.METHODS:This paper presents a critical review of recent computer vision-based marker-less human pose estimation systems with focus on their provided joint localization accuracy in comparison to physiotherapy requirements and ease of use. The accuracy, in terms of the capability to measure the knee angle, is analysed using simulation.RESULTS:Current pose estimation systems use 2D, 3D, multiple and single view-based techniques. The most promising techniques from a physiotherapy point of view are 3D marker-less pose estimation based on a single view as these can perform advanced motion analysis of the human body while only requiring a single camera and a computing device. Preliminary simulations reveal that some proposed systems already provide a sufficient accuracy for 2D joint angle estimations.CONCLUSIONS:Even though test results of different applications for some proposed techniques are promising, more rigour testing is required for validating their accuracy before they can be widely adopted in advanced rehabilitation applications.

Context: Using technical clothes with electrodes embedded in the clothing makes it possible to record the electrical activity produced by the activity of the skeletal muscles in activities of daily living. Objective: To investigate the reliability of measuring lower-limb left-right electromyography (EMG) activity ratio with smart shorts during stair descent, stair ascent, and repeated unloaded squats among healthy working-aged subjects. Methods: Seventeen females (mean age 25.5 y), and 17 males (mean age 29.9 y) participated in this test-retest protocol carried out twice on the same day. Results: Intraclass correlation coefficient (ICC) varied from .65 to .80 in the different activities. Mean difference and limits of agreement (LOA) between the repeated measurements were for descending stairs –0.8%, LOA –6.2% to 4.7%; for ascending stairs –0.9%, –6.5% to 4.7%; and for squats –0.2%, –5.4% to 4.9%. The coefficient of repeatability for descending stairs was 5.6%, for ascending stairs 5.7%, and for squats 5.3%. Conclusions: Our study among healthy subjects showed that the left-right EMG activity ratio in activities of daily living can be reliably measured with smart shorts. In future research, the feasibility of technical clothes as a follow-up method in rehabilitation should be investigated in greater detail.

Computer vision and its application is promising in several areas of health and well-being. Research within computer vision has made substantial progress during the past several decades, and will likely bring forward rapid advancements, especially when it comes to fast, real-time detection and recognition of different patterns or objects within health and well-being. This kind of real-time monitoring within computer vision has expanded rapidly during the last decades. The aim of this article is to present some of these advancements. Focus lies on current gesture recognition for realtime detection of human emotions and alertness, sign language translation, detection of safety critical incidents such as fall incident detection, functional vision aids for partially and fully blind persons, tele-surgery, computer vision based diagnostic health examination methods (endoscopy, photoplethysmography, and digital mammography), and computer vision based aids within rehabilitation. Recent research shows that computer vision based real-time monitoring is a valuable aid within many fields of health and well-being that enables and aids people. Computer vision is also an emerging research field and direction that requires multi-disciplinary collaboration and deployment of advanced machine learning methods.

Shortage of skilled healthcare personnel with the required Informationand communication technology competence have been common because of the fast pace of technological innovations. To ensure a sustainable and secure development in health and welfare, there is a need for future professionals to have an understanding of the new digital data on individuals, clients and patients that are emerging in healthcare with the new wearable devices. The aim of this article is to discuss the opportunities and challenges for professionals meeting the digital individual and the data produced on them by new wearable technologies. The road from patient to digital patient is today a challenge for both individuals and professionals, as well as for the society.

In rehabilitation stroke and Multiple sclerosis (MS) are two very common causes of motor disability in adults. Traditional rehabilitation is very time-consuming and expensive. Therefore, rehabilitation professionals are looking to Virtual Reality (VR) technology in order to assist patients on their path to function better in their daily lives. Recent studies have mostly investigated the end results of VR therapy, but the user experience has been less studied. This working paper presents a thematic review of recent studies to highlight the advantages and disadvantages of VR solutions in motor rehabilitation from the user perspective. Our findings suggest that VR rehabilitation can be more motivating for the patient than traditional rehabilitation, but current VR interventions are often overly simplistic and not customized for the user. This presents opportunities for innovative service design.