Home-based Rehabilitation System Research Articles

Clinical application research of intelligent monitoring system for knee rehabilitation: a randomized controlled trial

BackgroundThis study investigates the effectiveness of a self-developed intelligent monitoring system for home-based knee rehabilitation following total knee arthroplasty (TKA).MethodsIn this randomized controlled trial, 120 patients undergoing TKA were divided using random digit allocation. Preoperative and one-month postoperative assessments of knee function, quality of life, and isometric knee extension strength were conducted with the Intelligent Monitoring System. Patients received group-specific rehabilitation instructions pre-discharge and performed exercises for one month.ResultsChanges in isometric knee extensor strength on the affected side within one month post-surgery for the brace-monitored rehabilitation group showed a significant decrease three days after surgery compared to one day before surgery. Subsequent measurements taken at postoperative days 5, 7, 14, and 21 indicated a gradual increase in strength, although these increases did not reach statistical significance when compared with previous measurements. One month post-surgery, all groups demonstrated significant improvements in knee joint function and mobility compared to pre-surgery levels. Notably, the brace-monitored group showed statistically significant improvements in 36-Item Short-Form Health Survey (SF-36) scores over the conventional rehabilitation group.ConclusionsThe Intelligent Monitoring System provides effective real-time monitoring and guidance for home-based knee rehabilitation post-TKA. It significantly enhances knee joint function, isometric knee extension strength, and quality of life shortly after surgery compared to traditional rehabilitation methods. This system offers a promising approach for improving postoperative recovery in TKA patients.Trial registrationThis study was approved by the Medical Ethics Committee of Xiangya Hospital, Central South University (Ethics Approval Number 202209008-2). It was registered with the China Clinical Trial Registry, a primary registry of the World Health Organization’s International Clinical Trials Registry Platform (Registration Number ChiCTR2300068852).

A 2DoF robotic system for home-based upper limb rehabilitation

A 2DoF robotic system for home-based upper limb rehabilitation

Home-Based Rehabilitation of the Shoulder Using Auxiliary Systems and Artificial Intelligence: An Overview.

Advancements in modern medicine have bolstered the usage of home-based rehabilitation services for patients, particularly those recovering from diseases or conditions that necessitate a structured rehabilitation process. Understanding the technological factors that can influence the efficacy of home-based rehabilitation is crucial for optimizing patient outcomes. As technologies continue to evolve rapidly, it is imperative to document the current state of the art and elucidate the key features of the hardware and software employed in these rehabilitation systems. This narrative review aims to provide a summary of the modern technological trends and advancements in home-based shoulder rehabilitation scenarios. It specifically focuses on wearable devices, robots, exoskeletons, machine learning, virtual and augmented reality, and serious games. Through an in-depth analysis of existing literature and research, this review presents the state of the art in home-based rehabilitation systems, highlighting their strengths and limitations. Furthermore, this review proposes hypotheses and potential directions for future upgrades and enhancements in these technologies. By exploring the integration of these technologies into home-based rehabilitation, this review aims to shed light on the current landscape and offer insights into the future possibilities for improving patient outcomes and optimizing the effectiveness of home-based rehabilitation programs.

Use of the Digital Assistant Vigo in the Home Environment for Stroke Recovery: Focus Group Discussion With Specialists Working in Neurorehabilitation

There is a lack of resources for the provision of adequate rehabilitation after a stroke, thus creating a challenge to provide the necessary high-quality, patient-centered, and cost-efficient rehabilitation services at a time when they are needed the most. Tablet-based therapeutic programs present an alternative way to access rehabilitation services and show a new paradigm for providing therapeutic interventions following a stroke anytime and anywhere. The digital assistant Vigo is an artificial intelligence-based app that provides an opportunity for a new, more integrative way of carrying out a home-based rehabilitation program. Considering the complexity of the stroke recovery process, factors such as a suitable population, appropriate timing, setting, and the necessary patient-specialist support structure need to be thoroughly researched. There is a lack of qualitative research exploring the perspectives of professionals working in neurorehabilitation of the content and usability of the digital tool for the recovery of patients after a stroke. The aim of this study is to identify the requirements for a tablet-based home rehabilitation program for stroke recovery from the perspective of a specialist working in stroke rehabilitation. The focus group study method was chosen to explore specialists' attitudes, experience, and expectations related to the use of the digital assistant Vigo as a home-based rehabilitation program for stroke recovery in domains of the app's functionality, compliance, usability, and content. In total, 3 focus groups were conducted with a participant count of 5-6 per group and the duration of the discussion ranging from 70 to 80 minutes. In total, 17 health care professionals participated in the focus group discussions. The participants represented physiotherapists (n=7, 41.2%), occupational therapists (n=7, 41.2%), speech and language therapists (n=2, 11.8%), and physical medicine and rehabilitation physicians (n=1, 5.9%). Audio and video recordings of each discussion were created for further transcription and analysis. In total, 4 themes were identified: (1) the clinician's views on using Vigo as a home-based rehabilitation system, (2) patient-related circumstances facilitating and limiting the use of Vigo; (3) Vigo's functionality and use process (program creation, individual use, remote support); and (4) complementary and alternative Vigo use perspectives. The last 3 themes were divided further into 10 subthemes, and 2 subthemes had 2 sub-subthemes each. Health care professionals expressed a positive attitude toward the usability of the Vigo app. It is important that the content and use of the app be coherent with the aim to avoid (1) misunderstanding its practical use and the need for integration in practice and (2) misusing the app. In all focus groups, the importance of close involvement of rehabilitation specialists in the process of app development and research was highlighted.

Exercise Monitoring and Assessment System for Home-Based Respiratory Rehabilitation

Exercise training is a key component of respiratory rehabilitation. Exercise monitoring and assessment have shown to be beneficial and have significant improvement in the outcome of exercise training. In this article, we propose a noninvasive exercise monitoring and assessment system (EMAS) for home-based respiratory rehabilitation exercises. EMAS exploits multiband microwave sensing techniques to monitor in real-time the patient’s rehabilitation exercise training and synchronously provide online visual feedback for helping the patient better training. Then EMAS extracts exercise information (duration, intensity, and breathing changes) from all exercise data to assess the quality of rehabilitation exercise. We implement EMAS on the designed compact and portable prototypes and deploy it to monitor four subjects, resulting in one week of exercise data in total. System evaluations demonstrate that EMAS can accurately monitor rehabilitation exercises of each subject and obtain the exercise duration, exercise intensity, and breathing changes during rehabilitation exercises to achieve exercise assessment.

A novel home-based rehabilitative knee brace system is a viable option for postoperative rehabilitation after anterior cruciate ligament reconstruction: a report of 15 cases

PurposeTo investigate the functional outcomes for patients who used a novel home-based rehabilitative system during the postoperative period after anterior cruciate ligament (ACL) reconstructions.MethodsPatients undergoing ACL reconstruction surgeries were prospectively enrolled. A home-based rehabilitation system, which is composed of a knee brace with a motion tracker, a mobile app, and a web portal, was applied. Patients could complete the rehabilitation exercise through the audio guidance and the real-time tracking system which displayed the achieved motions on the user interface of the app. Feedbacks from the patients, including the International Knee Documentation Committee (IKDC) scores, were collected and uploaded to the web portal. Each patient would meet a specialized physical therapist face-to-face once a month. At postoperative 6 months, every patient received a GNRB arthrometer examination and a Cybex isokinetic dynamometer examination.ResultsA total of 15 patients (10 males and 5 females) were enrolled and followed for at least 6 months. The mean time of return to full knee extension was 1.5 months.The mean difference in laxity measured by GNRB arthrometer at 134 N significantly improved at postoperative 6 months (1.8 ± 1.6 mm) compared to that measured preoperatively (3.4 ± 1.9 mm) (p = 0.024). The peak torques of flexor and extensor muscles measured by Cybex isokinetic dynamometer remained unchanged at postoperative 6 months (p = 0.733 and 0.394, respectively). The patients’ IKDC score became smaller at postoperative 1 month (p = 0.011) and significantly improved at postoperative 6 months (p = 0.002).ConclusionUsing a home-based rehabilitative knee brace system after ACL reconstruction is a viable option as patients maintained their knee muscle strengths maintained their muscle strength and achieve similar or better knee range of motion six months postoperatively.

A Deep Learning Approach for Predicting Subject-Specific Human Skull Shape from Head Toward a Decision Support System for Home-Based Facial Rehabilitation

ObjectivePrediction of human skull shape from head is a complex and challenging engineering task for the development of a computer-aided vision system. Skull-to-face generation has been commonly performed in forensic facial reconstruction. Classical statistical approaches were usually used. However, the head-to-skull relationship is still misunderstood. Recently, novel deep learning (DL) models have showed their efficiency and robustness for a large range of applications. The present study aimed to develop a novel approach based on deep learning models to reconstruct the human skull shape from head. Material and methodsA head-to-skull generation workflow was developed and evaluated. A database of computed tomography (CT) images of 209 subjects was established for training and testing purposes. Three-dimension (3-D) head and skull geometries were reconstructed and then their respective descriptors (head/skull volumes, sampling feature points and point-to-center distances, head-skull thickness, Gaussian curvatures) were extracted. Two deep learning models (regression neural network and long-short term memory (LSTM)) were implemented and evaluated with different learning configurations. A 10-fold cross-validation was performed. Finally, the best and worst predicted cases were analyzed and discussed. ResultsThe mean errors from 10-fold cross-validation showed a better accuracy level for the regression neural network model according to the long short-term memory model. The mean error between the DL-predicted skull shapes and CT-based skull shapes ranges from 1.67 mm to 3.99 mm by using the regression deep learning model and the best learning configuration. The volume deviation between predicted skull shapes and CT-based skull shapes is smaller than 5%. ConclusionsThe present study suggested that regression deep learning model allows human skull to be predicted from a given head with a good level of accuracy. This opens new avenues for the rapid generation of human skull shape from visual sensors (e.g. Microsoft Kinect) toward a computer-aided vision system for facial mimic rehabilitation. As perspectives, muscle network will be incorporated into the present workflow. Then, facial mimic movements will be tracked and animated to evaluate and optimize the rehabilitation movements and exercises.

Design and Development of Intelligent Home Rehab Device for Post Stroke Therapy with Electro-Hydraulic Interventions Rehab Device for Post Stroke Therapy with Electro-Hydraulic Interventions

Today, brain attack disorders are one of the most life-threatening areas in the medical era, which mankind is facing nowadays. Globally, more than 10,000,000 people are subjected to brain attack disorders like hemiplegia and tremor, every year, where two-thirds of them survive. Among the survival community, more than 80 per cent of them are subjected to long-term impairment of their upper extremity. In order to treat the impairment, the survival group is subjected to medications and rehabilitation in order to improve their daily living. But the facilities are very limited in fast- developing countries like India when compared to western standards. The rehabilitation given corresponding with medications during the treatment period in hospitals does not give a complete recovery from disability. People from rural background could not meet their rehabilitation requirements even in the hospital during treatment and also when they are discharged to home after treatment from hospitals due to financial constraints and reachability. In order to motivate the survival group to fulfill their daily living and improve their lifestyle, this paper is focused on intelligent home-based rehabilitation system at low cost, reliability, and affordability. One major movement disorder namely Upper Arm Hemiplegia was taken into account and visited few major hospitals around Coimbatore and Chennai for literature and case study. The facilities available in various hospitals and their drawbacks were analyzed. Based on the studies conducted at hospitals and taking advice from therapists, an innovative low-cost home-based rehabilitation device using Electro-Hydraulic systems has been developed to support patients who were used to impaired living even after treatments. To support Upper Arm Hemiplegia patients, the devices which were developed and experimented to hold different functionalities are discussed in this paper.

Robotic Home-Based Rehabilitation Systems Design: From a Literature Review to a Conceptual Framework for Community-Based Remote Therapy During COVID-19 Pandemic.

During the COVID-19 pandemic, the higher susceptibility of post-stroke patients to infection calls for extra safety precautions. Despite the imposed restrictions, early neurorehabilitation cannot be postponed due to its paramount importance for improving motor and functional recovery chances. Utilizing accessible state-of-the-art technologies, home-based rehabilitation devices are proposed as a sustainable solution in the current crisis. In this paper, a comprehensive review on developed home-based rehabilitation technologies of the last 10 years (2011–2020), categorizing them into upper and lower limb devices and considering both commercialized and state-of-the-art realms. Mechatronic, control, and software aspects of the system are discussed to provide a classified roadmap for home-based systems development. Subsequently, a conceptual framework on the development of smart and intelligent community-based home rehabilitation systems based on novel mechatronic technologies is proposed. In this framework, each rehabilitation device acts as an agent in the network, using the internet of things (IoT) technologies, which facilitates learning from the recorded data of the other agents, as well as the tele-supervision of the treatment by an expert. The presented design paradigm based on the above-mentioned leading technologies could lead to the development of promising home rehabilitation systems, which encourage stroke survivors to engage in under-supervised or unsupervised therapeutic activities.

Investigating the User Experience of Virtual Reality Rehabilitation Solution for Biomechatronics Laboratory and Home Environment

Virtual reality (VR) technology is a promising tool in physical rehabilitation. Research indicates that VR-supported rehabilitation is beneficial for task-specific training, multi-sensory feedback, diversified rehabilitation tasks, and patient motivation. Our first goal was to create a biomechatronics laboratory with a VR setup for increasing immersion and a motion platform to provide realistic feedback to patients. The second goal was to investigate possibilities to replicate features of the biomechatronics laboratory in a home-based training system using commercially available components. The laboratory comprises of a motion platform with 6-degrees-of-freedom (Rexroth eMotion), fitted with a load cell integrated treadmill, and an Oculus Quest virtual reality headset. The load cells provide input for data collection, as well as VR motion control. The home-based rehabilitation system consists of a Nintendo Wii Balance Board and an Oculus Rift virtual reality headset. User studies in the laboratory and home environment used direct observation techniques and self-reported attitudinal research methods to assess the solution’s usability and user experience. The findings indicate that the proposed VR solution is feasible. Participants using the home-based system experienced more cybersickness and imbalance compared to those using the biomechatronics laboratory solution. Future studies will look at a setup that is safe for first patient studies, and exercises to improve diagnosis of patients and progress during rehabilitation.

A Home-Based Bilateral Rehabilitation System With sEMG-based Real-Time Variable Stiffness.

Bilateral rehabilitation allows patients with hemiparesis to exploit the cooperative capabilities of both arms to promote the recovery process. Although various approaches have been proposed to facilitate synchronized robot-assisted bilateral movements, few studies have focused on addressing the varying joint stiffness resulting from dynamic motions. This paper presents a novel bilateral rehabilitation system that implements a surface electromyography (sEMG)-based stiffness control to achieve real-time stiffness adjustment based on the user's dynamic motion. An sEMG-driven musculoskeletal model that incorporates the muscle activation and muscular contraction dynamics is developed to provide reference signals for the robot's real-time stiffness control. Preliminary experiments were conducted to evaluate the system performance in tracking accuracy and comfortability, which showed the proposed rehabilitation system with sEMG-based real-time stiffness variation achieved fast adaption to the patient's dynamic movement as well as improving the comfort in robot-assisted bilateral training.

Wearable triboelectric nanogenerator based exercise system for upper limb rehabilitation post neurological injuries

Recent rehabilitation methods for physical impairments utilize various technologies such as robotic devices and gaming software in order to assist, motivate, and facilitate the recovery process. While most of the rehabilitation devices require external power sources, the triboelectric nanogenerator (TENG) has been proven as a reliable self-powered sensor that can also be used as an energy harvester. In this work, we utilize the TENG as a game controller as well as an exercise device for patients undergoing rehabilitation. We show that since the TENG can store energy, it serves as a motivating factor for the patient, as well as an index to monitor progression of rehabilitation and any improvements they make during rehabilitation. First, we describe the working principle of the TENG-based rehabilitation device (Rehab-TENG) and perform parametric studies to determine the performance of the device. Second, we developed a circuit to digitize the TENG output so that the patient could use the Rehab-TENG to control a computer game via Bluetooth. Third, the Rehab-TENG was employed as an energy harvester in an exercise system, where the patient moved their impaired arm to store energy into a capacitor. Based on the speed of capacitor charging, the level of impairment could be estimated. Finally, the patients were asked to answer a questionnaire where they emphasized the practicability of the device for its use as a home-based rehabilitation system and the harvesting of energy as a motivating factor for them to move their impaired body part more than they normally would. We expect this study will enhance the potential of TENG use in healthcare as a practical tool for patient rehabilitation.

Fugl Meyer Assessment for Paralytic Glove with Micro Motor Configurations to Assist Post Stroke Therapy

Today, brain attack disorders are one of the most life-threatening areas in the medical era, which the mankind is facing nowadays. Globally, more than 10, 00,000people are subjected to brain attack disorders like hemiplegia and tremor, every year, where two-thirds of them survive. Among the survival community, more than 80 per cent of them are subjected to long-term impairment of their upper extremity. In order to treat the impairment, the survival group is subjected to medications and rehabilitation in order to improve their daily living. But the facilities are very limited in fast- developing countries like India when compared to western standards. The rehabilitation given in corresponding with medications during the treatment period in hospitals does not give a complete recovery from disability. People from rural background could not meet their rehabilitation requirements even in the hospital during treatment and also when they are discharged to home after treatment from hospitals due to financial constraints and reachability. In order to motivate the survival group to fulfill their daily living and improve their lifestyle, this paper is focused on intelligent home-based rehabilitation system at low cost, reliability, and affordability. One major movement disorder namely Upper Arm Hemiplegia was taken into account and visited few major hospitals around Coimbatore and Chennai for literature and case study. The facilities available in various hospitals and their drawbacks were analyzed. Based on the studies conducted at hospitals and taking advice from therapists, an innovative low-cost home- based rehabilitation device using Electro-Mechanical systems has been developed to support samples who were used to impaired living even after treatments. To support Upper Arm Hemiplegia patients, the devices which were developed and experimented with Fugl Meyer Assessment to analyse the improvements in different functionalities are discussed in this paper.

Home-Based Rehabilitation System for Stroke Survivors: A Clinical Evaluation.

Recently, a home-based rehabilitation system for stroke survivors (Baptista et al. Comput. Meth. Prog. Biomed. 176:111-120 2019), composed of two linked applications (one for the therapist and another one for the patient), has been introduced. The proposed system has been previously tested on healthy subjects. However, for a fair evaluation, it is necessary to carry out a clinical study considering stroke survivors. This work aims at evaluating the home-based rehabilitation system on 10 chronic post-stroke spastic patients. For this purpose, each patient carries out two exercises implying the motion of the spastic upper limb using the home-based rehabilitation system. The impact of the color-based 3D skeletal feedback, guiding the patients during the training, is studied. The Time Variable Replacement (TVR)-based average distance, as well as the average postural angle used in Baptista et al. (Comput. Meth. Prog. Biomed. 176:111-120 2019), are reported to compare the movement and the posture of the patient with and without showing the feedback proposals, respectively. Furthermore, three different questionnaires, specifically designed for this study, are used to evaluate the user experience of the therapist and the patients. Overall, the reported results suggest the relevance of the proposed system for home-based rehabilitation of stroke survivors.

End-effector wheeled robotic arm gaming prototype for upper limb coordination control in home-based therapy

The stroke patient will be having difficulty to control their upper limb, which causes their handling to become weak and unorganized. Conventional therapy designed to retrain the subject ability when it's losses due to stroke. As previous study concern that a subject with strong motivation and concentration of treatment tends to recover better than people who don't follow the program. This research focused on intensifying the training by providing user with Wheel robotic arm to train their upper limb. User will be asked to do exercising on moving particular objects to another position repetitively during a specific period. The robot will help the user to assist and relearn their motoric skill and improve muscle strength and coordination. The result of training is quite convincing when the user gives a positive response toward the practice. Around 86 percent of subject likely prefer the proposed system as their home-based rehabilitation system. The Anova testing with alpha 0.05 shows that there is no significant difference between trained subject and untrained subject on operating the wheeled robotic arm. It's mean the proposed system is reliable and user friendly to be used without an assistant so user can have more flexibility and improve their accomplishment on regaining their motoric skills. The future work will focus on stroke patient testing with more challenge and obstacle in enhancing the effectiveness of the stroke rehabilitation system.

Experimental Validation of a Contactless Finger Displacement Measurement System Using Electrical Near-Field Sensing

This research investigates the potential of contactless finger motion measurement, focusing particularly on ease of use to improve the success of home-based hand rehabilitation exercises. Previously, a mathematical model was developed based on a finite-element method simulation. This article validates this model on multifinger noncontact measuring under laboratory conditions. Twenty-three healthy subjects with normal hand and finger functions participated. An independent near-field distance measurement was developed and compared with the output from an optical sensor. It was observed from the experiment that the prediction model worked well with the measuring system reported here. The average uncertainties of measurement using the prediction model are 0.68 and 0.55 mm, which are 3.5% and 2.7% of the full-scale range for the index finger and middle finger, respectively. The results from the experiment show that the reported system is capable of measuring the small movements of fingers. With the combination of the noncontact measuring feature and the lack of complicated setup, this system is easy-to-use as the basis of a home-based independent rehabilitation system.

Evaluation of Home-Based Rehabilitation Sensing Systems with Respect to Standardised Clinical Tests.

With increased demand for tele-rehabilitation, many autonomous home-based rehabilitation systems have appeared recently. Many of these systems, however, suffer from lack of patient acceptance and engagement or fail to provide satisfactory accuracy; both are needed for appropriate diagnostics. This paper first provides a detailed discussion of current sensor-based home-based rehabilitation systems with respect to four recently established criteria for wide acceptance and long engagement. A methodological procedure is then proposed for the evaluation of accuracy of portable sensing home-based rehabilitation systems, in line with medically-approved tests and recommendations. For experiments, we deploy an in-house low-cost sensing system meeting the four criteria of acceptance to demonstrate the effectiveness of the proposed evaluation methodology. We observe that the deployed sensor system has limitations in sensing fast movement. Indicators of enhanced motivation and engagement are recorded through the questionnaire responses with more than of the respondents supporting the system’s motivation and engagement enhancement. The evaluation results demonstrate that the deployed system is fit for purpose with statistically significant (, , ) and unbiased correlation to the golden standard.

Autonomous Use of the Home Virtual Rehabilitation System: A Feasibility and Pilot Study

Objective: This article describes the findings of a study examining the ability of persons with strokes to use home virtual rehabilitation system (HoVRS), a home-based rehabilitation system, and the impact of motivational enhancement techniques on subjects' motivation, adherence, and motor function improvements subsequent to a 3-month training program. Materials and Methods: HoVRS integrates a Leap Motion controller, a passive arm support, and a suite of custom-designed hand rehabilitation simulations. For this study, we developed a library of three simulations, which include activities such as flexing and extending fingers to move a car, flying a plane with wrist movement, and controlling an avatar running in a maze using reaching movements. Two groups of subjects, the enhanced motivation (EM) group and the unenhanced control (UC) group, used the system for 12 weeks in their homes. The EM group trained using three simulations that provided 8-12 levels of difficulty and complexity. Graphics and scoring opportunities increased at each new level. The UC group performed the same simulations, but difficulty was increased utilizing an algorithm that increased difficulty incrementally, making adjustments imperceptible. Results: Adherence to both the EM and UC protocols exceeded adherence to home exercise programs described in the stroke rehabilitation literature. Both groups demonstrated improvements in upper extremity function. Intrinsic motivation levels were better for the EM group and motivation levels were maintained for the 12-week protocol. Conclusion: A 12-week home-based training program using HoVRS was feasible. Motivational enhancement may have a positive impact on motivation, adherence, and motor outcome.

MRehab, Designing and Using Technology in a HomeBased Stroke Rehabilitation Program

Aim 1. To assess usability of a portable home-based functional rehabilitation system, mRehab, consisting of a smartphone app and three dimensional printed objects.

Understanding User Requirements for the Design of a Home-Based Stroke Rehabilitation System.

Limitations following stroke make it one of the leading causes of disability. The current medical pathway provides intensive care in the acute stages, but rehabilitation services are commonly discontinued after one year. While written home exercise programs are regularly prescribed at the time of discharge, compliancy is an issue. The goal of this study was to inform the design of a home-based portable rehabilitation system based on feedback from individuals with stroke and clinicians. A main component under consideration is the type and format of information feedback provided to the user, as this is hypothesized to support compliance with the rehabilitation program. From a series of focus groups and usability testing, a set of design requirements for the hardware and software were constructed. Essential features mentioned for the feedback interface included: task completion time, quality of movement, a selection of exercises, goal tracking, and a display of historical data.