Smart Rehabilitation Garment for posture monitoring

Use of commercially available wearable devices for physical rehabilitation in healthcare: a systematic review

OBJECTIVES

To evaluate whether commercially available 'off-the-shelf' wearable technology can improve patient rehabilitation outcomes, and to categorise all wearables currently being used to augment rehabilitation, including the disciplines and conditions under investigation.

DESIGN

Systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis 2020 statement checklist, and using the Grading of Recommendations, Assessment, Development and Evaluation approach.

DATA SOURCES

Embase, MEDLINE, Web of Science and the Cochrane Library were searched up to and including July 2023.

ELIGIBILITY CRITERIA

We included trials and observational studies evaluating the use of consumer-grade wearables, in real patient cohorts, to aid physical therapy or rehabilitation. Only studies investigating rehabilitation of acute events with defined recovery affecting adult patients were included.

DATA EXTRACTION AND SYNTHESIS

Two independent reviewers used a standardised protocol to search, screen and extract data from the included studies. Risk of bias was assessed using the Cochrane Methods Risk of Bias in Randomised Trials V.2 and Risk of Bias in Non-Randomised Studies of Interventions tools for randomised controlled trials (RCTs) and observational studies, respectively.

RESULTS

Eighteen studies encompassing 1754 patients met eligibility criteria, including six RCTs, six quasi-experimental studies and six observational studies. Eight studies used wearables in Orthopaedics, seven in Stroke Medicine, two in Oncology and one in General Surgery. All six RCTs demonstrated that wearable-driven feedback increases physical activity. Step count was the most common measure of physical activity. Two RCTs in orthopaedics demonstrated non-inferiority of wearable self-directed rehabilitation compared with traditional physiotherapy, highlighting the potential of wearables as alternatives to traditional physiotherapy. All 12 non-randomised studies demonstrated the feasibility and acceptability of wearable-driven self-directed rehabilitation.

CONCLUSION

This review demonstrates that consumer-grade wearables can be used as adjuncts to traditional physiotherapy, and potentially as alternatives for self-directed rehabilitation of non-chronic conditions. Better designed studies, and larger RCTs, with a focus on economic evaluations are needed before a case can be made for their widespread adoption in healthcare settings.

PROSPERO REGISTRATION ID

CRD42023459567.

Integrating sEMG and IMU Sensors in an e-Textile Smart Vest for Forward Posture Monitoring: First Steps

Currently, the market for wearable devices is expanding, with a growing trend towards the use of these devices for continuous-monitoring applications. Among these, real-time posture monitoring and assessment stands out as a crucial application given the rising prevalence of conditions like forward head posture (FHP). This paper proposes a wearable device that combines the acquisition of electromyographic signals from the cervical region with inertial data from inertial measurement units (IMUs) to assess the occurrence of FHP. To improve electronics integration and wearability, e-textiles are explored for the development of surface electrodes and conductive tracks that connect the different electronic modules. Tensile strength and abrasion tests of 22 samples consisting of textile electrodes and conductive tracks produced with three fiber types (two from Shieldex and one from Imbut) were conducted. Imbut's Elitex fiber outperformed Shieldex's fibers in both tests. The developed surface electromyography (sEMG) acquisition hardware and textile electrodes were also tested and benchmarked against an electromyography (EMG) gold standard in dynamic and isometric conditions, with results showing slightly better root mean square error (RMSE) values (for 4 × 2 textile electrodes (10.02%) in comparison to commercial Ag/AgCl electrodes (11.11%). The posture monitoring module was also validated in terms of joint angle estimation and presented an overall error of 4.77° for a controlled angular velocity of 40°/s as benchmarked against a UR10 robotic arm.

Wearables for Monitoring and Postural Feedback in the Work Context: A Scoping Review

Wearables offer a promising solution for simultaneous posture monitoring and/or corrective feedback. The main objective was to identify, synthesise, and characterise the wearables used in the workplace to monitor and postural feedback to workers. The PRISMA-ScR guidelines were followed. Studies were included between 1 January 2000 and 22 March 2023 in Spanish, French, English, and Portuguese without geographical restriction. The databases selected for the research were PubMed®, Web of Science®, Scopus®, and Google Scholar®. Qualitative studies, theses, reviews, and meta-analyses were excluded. Twelve studies were included, involving a total of 304 workers, mostly health professionals (n = 8). The remaining studies covered workers in the industry (n = 2), in the construction (n = 1), and welders (n = 1). For assessment purposes, most studies used one (n = 5) or two sensors (n = 5) characterised as accelerometers (n = 7), sixaxial (n = 2) or nonaxialinertial measurement units (n = 3). The most common source of feedback was the sensor itself (n = 6) or smartphones (n = 4). Haptic feedback was the most prevalent (n = 6), followed by auditory (n = 5) and visual (n = 3). Most studies employed prototype wearables emphasising kinematic variables of human movement. Healthcare professionals were the primary focus of the study along with haptic feedback that proved to be the most common and effective method for correcting posture during work activities.

Vibration motor stimulation device in smart leggings that promotes motor performance in older people

Globally, accelerated aging is taking place alongside increased life expectancy of the population. This poses a challenge to maintaining autonomy and independence as people age but preventing falls and disabilities. Currently, there are few specific technologies on the market that are focused on the rehabilitation and promotion of autonomy in older adults. This study presents the development of a prototype (Myoviber®) of a low-cost, wearable everyday garment, designed to stimulate the lower limbs by the application of focal muscle vibration and incorporating technical textile qualities. The presented approach is proactive and preventive, maintaining functionality for the elderly while integrating electronic technology into an everyday garment. For this, a comprehensive study was carried out that included the design of the leggings through anthropometric analyses, the development of vibration devices at a stable frequency located in the knee extensor muscle and a smart belt with wireless connection, and the optimization of the battery autonomy. The development of the prototype was carried out through the construction of a vibratory device, which was validated with biomechanical evaluations. The results show an increase in the functional capacity of the lower limbs, in relation to motor tasks such as postural balance and gait in older people.

Artificial Intelligence of Things- (AIoT-) Based Patient Activity Tracking System for Remote Patient Monitoring

Telehealth and remote patient monitoring (RPM) have been critical components that have received substantial attention and gained hold since the pandemic's beginning. Telehealth and RPM allow easy access to patient data and help provide high-quality care to patients at a low cost. This article proposes an Intelligent Remote Patient Activity Tracking System system that can monitor patient activities and vitals during those activities based on the attached sensors. An Internet of Things- (IoT-) enabled health monitoring device is designed using machine learning models to track patient's activities such as running, sleeping, walking, and exercising, the vitals during those activities such as body temperature and heart rate, and the patient's breathing pattern during such activities. Machine learning models are used to identify different activities of the patient and analyze the patient's respiratory health during various activities. Currently, the machine learning models are used to detect cough and healthy breathing only. A web application is also designed to track the data uploaded by the proposed devices.

A Wearable System Composed of FBG-Based Soft Sensors for Trunk Compensatory Movements Detection in Post-Stroke Hemiplegic Patients

In this study, a novel wearable system for the identification of compensatory trunk movements (CTMs) in post-stroke hemiplegic patients is presented. The device is composed of seven soft sensing elements (SSEs) based on fiber Bragg grating (FBG) technology. Each SSE consists of a single FBG encapsulated into a flexible matrix to enhance the sensor’s robustness and improve its compliance with the human body. The FBG’s small size, light weight, multiplexing capability, and biocompatibility make the proposed wearable system suitable for multi-point measurements without any movement restriction. Firstly, its manufacturing process is presented, together with the SSEs’ mechanical characterization to strain. Results of the metrological characterization showed a linear response of each SSE in the operating range. Then, the feasibility assessment of the proposed system is described. In particular, the device’s capability of detecting CTMs was assessed on 10 healthy volunteers and eight hemiplegic patients while performing three tasks which are representative of typical everyday life actions. The wearable system showed good potential in detecting CTMs. This promising result may foster the use of the proposed device on post-stroke patients, aiming at assessing the proper course of the rehabilitation process both in clinical and domestic settings. Moreover, its use may aid in defining tailored strategies to improve post-stoke patients’ motor recovery and quality of life.

Smart sensor tights: Movement tracking of the lower limbs in football

This article presents a novel smart sensor garment with integrated miniaturized inertial measurements units (IMUs) that can be used to monitor lower body kinematics during daily training activities, without the need of extensive technical assistance throughout the measurements. The smart sensor tights enclose five ultra-light sensor modules that measure linear accelerations, angular velocities, and the earth magnetic field in three directions. The modules are located at the pelvis, thighs, and shanks. The garment enables continuous measurement in the field at high sample rates (250 Hz) and the sensors have a large measurement range (32 g, 4,000°/s). They are read out by a central processing unit through an SPI bus, and connected to a centralized battery in the waistband. A fully functioning prototype was built to perform validation studies in a lab setting and in a field setting. In the lab validation study, the IMU data (converted to limb orientation data) were compared with the kinematic data of an optoelectronic measurement system and good validity (CMCs >0.8) was shown. In the field tests, participants experienced the tights as comfortable to wear and they did not feel restricted in their movements. These results show the potential of using the smart sensor tights on a regular base to derive lower limb kinematics in the field.

Posture Feedback System with Wearable Speaker

Maintaining good posture when using a laptop or a smartphone can prevent computer vision syndrome and text neck syndrome. However, it is difficult to remain aware of posture during an activity. Thus, wearable systems with posture feedback can help maintain good posture during daily activities. In this paper, we propose a posture feedback system that uses a commercial wearable speaker, which has been used for music and video conferencing when working from home. To judge a user's posture as good or poor, we focus on estimating the distance between the user's eyes and the screen when using a laptop and the neck tilt when using a smartphone. To estimate the distance, we use an active sensing method with ultrasound sent from a wearable speaker to a microphone on a laptop or a smartphone. The sound pressure of ultrasound changes depending on the distance between the wearable speaker and the microphone. In addition, an active sensing method can be used to estimate neck tilt because the sound pressure changes depending on the angle between the wearable speaker and the microphone. When the system judges the user's posture as poor, it will provide auditory feedback by applying digital audio effects to audible sounds (i.e., audio being listened to). Audio signal processing is implemented as a web application so users can use our system easily and immediately. We conducted three experiments to verify the feasibility of our proposed method. The sound pressure changed depending on the distance and angle between a wearable speaker and a microphone, and the system could judge posture as good or poor at almost 100 % under the experimental conditions.

Sensors for Context-Aware Smart Healthcare: A Security Perspective

The advances in the miniaturisation of electronic devices and the deployment of cheaper and faster data networks have propelled environments augmented with contextual and real-time information, such as smart homes and smart cities. These context-aware environments have opened the door to numerous opportunities for providing added-value, accurate and personalised services to citizens. In particular, smart healthcare, regarded as the natural evolution of electronic health and mobile health, contributes to enhance medical services and people's welfare, while shortening waiting times and decreasing healthcare expenditure. However, the large number, variety and complexity of devices and systems involved in smart health systems involve a number of challenging considerations to be considered, particularly from security and privacy perspectives. To this aim, this article provides a thorough technical review on the deployment of secure smart health services, ranging from the very collection of sensors data (either related to the medical conditions of individuals or to their immediate context), the transmission of these data through wireless communication networks, to the final storage and analysis of such information in the appropriate health information systems. As a result, we provide practitioners with a comprehensive overview of the existing vulnerabilities and solutions in the technical side of smart healthcare.

Evidence for the Effectiveness of Feedback from Wearable Inertial Sensors during Work-Related Activities: A Scoping Review

Background: Wearable inertial sensor technology (WIST) systems provide feedback, aiming to modify aberrant postures and movements. The literature on the effects of feedback from WIST during work or work-related activities has not been previously summarised. This review examines the effectiveness of feedback on upper body kinematics during work or work-related activities, along with the wearability and a quantification of the kinematics of the related device. Methods: The Cinahl, Cochrane, Embase, Medline, Scopus, Sportdiscus and Google Scholar databases were searched, including reports from January 2005 to July 2021. The included studies were summarised descriptively and the evidence was assessed. Results: Fourteen included studies demonstrated a 'limited' level of evidence supporting posture and/or movement behaviour improvements using WIST feedback, with no improvements in pain. One study assessed wearability and another two investigated comfort. Studies used tri-axial accelerometers or IMU integration (n = 5 studies). Visual and/or vibrotactile feedback was mostly used. Most studies had a risk of bias, lacked detail for methodological reproducibility and displayed inconsistent reporting of sensor technology, with validation provided only in one study. Thus, we have proposed a minimum 'Technology and Design Checklist' for reporting. Conclusions: Our findings suggest that WIST may improve posture, though not pain; however, the quality of the studies limits the strength of this conclusion. Wearability evaluations are needed for the translation of WIST outcomes. Minimum reporting standards for WIST should be followed to ensure methodological reproducibility.

The past, present, and future of remote patient monitoring in spine care: an overview

PURPOSE

Remote patient monitoring (RPM) has revolutionized the landscape of healthcare. From humble beginnings rooted in landline home telephone calls to present-day devices with near instantaneous wireless connectivity, the evolution of technology has ushered in an era of digital medicine and remote care. Presently, a vast array of healthcare data points can be automatically generated, analyzed, and forwarded to providers to supplement clinical decision-making. While RPM originated and was popularized within medicine, its role in orthopedics, and particularly within spine surgery, is evolving. We sought to provide an overview of RPM within orthopedics, with specific attention on spine care, analyzing its origins, present-day form, and prospects.

METHODS

We reviewed the literature to date as it pertains to RPM within healthcare at large, orthopedics, and spine care.

RESULTS

We detail the development and clinical use of wearable technology and smart implants, examining the underlying technology and evaluating the spectrum of their present-day and potential applications.

CONCLUSIONS

Technological advancements are not only reshaping the paradigm of musculoskeletal care but are also redefining the physician-patient relationship as well as reimagining traditional perspectives on healthcare data collection and privacy.

Effects of smart garments on the well-being of athletes: a scoping review protocol

INTRODUCTION

With the advancements in wearable electronics, electronically integrated smart garments started to transpire in our daily lives. Smart garment technologies are incorporated into sportswear applications to enhance the well-being and performance of athletes. Smart garments applications in the sports sector are increasing, and the variety of smart garment applications available in the literature is overwhelming. Therefore, it is essential to compare the vast array of technologies incorporated in smart garments for athletes to understand the knowledge gaps for future studies. The protocol paper aims to examine the smart garments used in the sports domain to enhance the health and well-being of athletes.

METHODS AND ANALYSIS

Relevant studies will be retrieved using predefined search terms from Scopus, Web of Science, Science Direct, PubMed and IEEE Xplore. The retrieved articles will be eliminated in two phases: title and abstract screening and full-text screening. The included articles will be primary studies published in the English language within the last 10 years. Subsequently, the included articles will be further studied to extract data using a data extraction form. The extracted data will undergo a thematic analysis. Also, quantitative analysis will be carried out using descriptive statistics.

ETHICS AND DISSEMINATION

The results of this review will provide a comprehensive understanding of smart garment concepts used in the sports domain. The findings of this scoping review will be shared through a journal publication and a conference presentation. Ethical approval is not needed for this scoping review.

PROTOCOL REGISTRATION NUMBER

DOI 10.17605/OSF.IO/34MF2 (https://osf.io/34mf2).

A Theoretical Framework and Conceptual Design for Engaging Children in Therapy at Home-The Design of a Wearable Breathing Trainer

Wearable technologies are being implemented in the health and medical context with increasing frequency. Such technologies offer valuable opportunities to stimulate self-management in these domains. In this context, engagement plays a crucial role. An engaged patient is a patient who is emotionally involved and committed to the therapy or care process. Particularly for children who have to follow some sort of therapy, engagement is important to ensure a successful outcome of the therapy. To design for engagement, a framework based on theories of motivation in child therapy was developed. This framework was applied to the design of a wearable breathing trainer for children with asthma and dysfunctional breathing. As such, the present paper provides knowledge about the implementation of theory on engagement and motivation in design. Expert and first user evaluations found that the resulting prototype is appealing, perceived as useful, and may engage children in breathing training and stimulate self-management.

Stroke Patients' Acceptance of a Smart Garment for Supporting Upper Extremity Rehabilitation

The objective is to evaluate to which extent that Zishi a garment equipped with sensors that can support posture monitoring can be used in upper extremity rehabilitation training of stroke patients. Seventeen stroke survivors (mean age: 55 years old, SD =13.5) were recruited in three hospitals in Shanghai. Patients performed 4 tasks (analytical shoulder flexion, functional shoulder flexion placing a cooking pot, analytical flexion in the scapular plane, and functional flexion in the scapular plane placing a bottle of water) with guided feedback on a tablet that was provided through inertial sensors embedded in the Zishi system at the scapula and the thoracic spine region. After performing the training tasks, patients completed four questionnaires for assessing their motivation, their acceptance of the system, its credibility, and usability. The study participants were highly motivated to train with Zishi and the system was rated high usability, while the subjects had moderate confidence with technology supported training in comparison with the training with therapists. The patients respond positively to using Zishi to support rehabilitation training in a clinical setting. Further developments need to address more on engaging and adaptive feedback. This paper paves the way for larger scale effectiveness studies.

Detection of Infantile Movement Disorders in Video Data Using Deformable Part-Based Model

Movement analysis of infants' body parts is momentous for the early detection of various movement disorders such as cerebral palsy. Most existing techniques are either marker-based or use wearable sensors to analyze the movement disorders. Such techniques work well for adults, however they are not effective for infants as wearing such sensors or markers may cause discomfort to them, affecting their natural movements. This paper presents a method to help the clinicians for the early detection of movement disorders in infants. The proposed method is marker-less and does not use any wearable sensors which makes it ideal for the analysis of body parts movement in infants. The algorithm is based on the deformable part-based model to detect the body parts and track them in the subsequent frames of the video to encode the motion information. The proposed algorithm learns a model using a set of part filters and spatial relations between the body parts. In particular, it forms a mixture of part-filters for each body part to determine its orientation which is used to detect the parts and analyze their movements by tracking them in the temporal direction. The model is represented using a tree-structured graph and the learning process is carried out using the structured support vector machine. The proposed framework will assist the clinicians and the general practitioners in the early detection of infantile movement disorders. The performance evaluation of the proposed method is carried out on a large dataset and the results compared with the existing techniques demonstrate its effectiveness.

Smart mat system with pressure sensor array for unobtrusive sleep monitoring

To improve the unobtrusiveness and comfortableness of sleep monitoring, we proposed the design and implementation of a smart mat which utilized flexible pressure sensor array and printed electrodes to monitor physiological and behavioral data during sleep. With the proposed novel soft seven-layer structure, the smart mat system can measure pressure distribution images and calculate respiratory rate of subjects. The function of this system was realized with pressure acquisition circuit controlled by Arduino processor. Experiments for pressure distribution tests and respiratory rate measurements were carried out to validate the performance of the proposed system. The experimental results demonstrated that the smart mat could be a viable option for unobtrusive sleep monitoring in the future.

A Novel Cardiac Auscultation Monitoring System Based on Wireless Sensing for Healthcare

Heart sounds deliver vital physiological and pathological evidence about health. Wireless cardiac auscultation offers continuous cardiac monitoring of an individual without 24*7 manual healthcare care services. In this paper, a novel wireless sensing system to monitor and analyze cardiac condition is proposed, which sends the information to the caregiver as well as a medical practitioner with an application of the Internet of Things (IoT). An integrated system for heart sound acquisition, storage, and asynchronous analysis has been developed, from scratch to information uploading through IoT and signal analysis. Cardiac auscultation sensing unit has been designed to monitor cardiovascular health of an individual. Bluetooth protocol is used to offer power efficiency and moderate data transmission rate. The Hilbert-Huang transform is used to eliminate interference signals and to help to extract the heart sound signal features. Subsequence segmentation algorithm based on double-threshold has been developed to extract physiological parameters. Preprocessing, segmentation, and clustering technique were performed for significant health information interpretation. The cardiac auscultation monitoring system may provide a way for heart disease self-management.

A Compressed Sensing Based Method for Reducing the Sampling Time of A High Resolution Pressure Sensor Array System

For extracting the pressure distribution image and respiratory waveform unobtrusively and comfortably, we proposed a smart mat which utilized a flexible pressure sensor array, printed electrodes and novel soft seven-layer structure to monitor those physiological information. However, in order to obtain high-resolution pressure distribution and more accurate respiratory waveform, it needs more time to acquire the pressure signal of all the pressure sensors embedded in the smart mat. In order to reduce the sampling time while keeping the same resolution and accuracy, a novel method based on compressed sensing (CS) theory was proposed. By utilizing the CS based method, 40% of the sampling time can be decreased by means of acquiring nearly one-third of original sampling points. Then several experiments were carried out to validate the performance of the CS based method. While less than one-third of original sampling points were measured, the correlation degree coefficient between reconstructed respiratory waveform and original waveform can achieve 0.9078, and the accuracy of the respiratory rate (RR) extracted from the reconstructed respiratory waveform can reach 95.54%. The experimental results demonstrated that the novel method can fit the high resolution smart mat system and be a viable option for reducing the sampling time of the pressure sensor array.

Motor Control Training for the Shoulder with Smart Garments

Wearable technologies for posture monitoring and posture correction are emerging as a way to support and enhance physical therapy treatment, e.g., for motor control training in neurological disorders or for treating musculoskeletal disorders, such as shoulder, neck, or lower back pain. Among the various technological options for posture monitoring, wearable systems offer potential advantages regarding mobility, use in different contexts and sustained tracking in daily life. We describe the design of a smart garment named Zishi to monitor compensatory movements and evaluate its applicability for shoulder motor control training in a clinical setting. Five physiotherapists and eight patients with musculoskeletal shoulder pain participated in the study. The attitudes of patients and therapists towards the system were measured using standardized survey instruments. The results indicate that patients and their therapists consider Zishi a credible aid for rehabilitation and patients expect it will help towards their recovery. The system was perceived as highly usable and patients were motivated to train with the system. Future research efforts on the improvement of the customization of feedback location and modality, and on the evaluation of Zishi as support for motor learning in shoulder patients, should be made.