Gait Analysis Using Wearable Sensors

Gait analysis using wearable sensors is an inexpensive, convenient, and efficient manner of providing useful information for multiple health-related applications. As a clinical tool applied in the rehabilitation and diagnosis of medical conditions and sport activities, gait analysis using wearable sensors shows great prospects. The current paper reviews available wearable sensors and ambulatory gait analysis methods based on the various wearable sensors. After an introduction of the gait phases, the principles and features of wearable sensors used in gait analysis are provided. The gait analysis methods based on wearable sensors is divided into gait kinematics, gait kinetics, and electromyography. Studies on the current methods are reviewed, and applications in sports, rehabilitation, and clinical diagnosis are summarized separately. With the development of sensor technology and the analysis method, gait analysis using wearable sensors is expected to play an increasingly important role in clinical applications

Development of a mobile technology system to measure shoulder range of motion

In patients with shoulder movement impairment, assessing and monitoring shoulder range of motion is important for determining the severity of impairments due to disease or injury and evaluating the effects of interventions. Current clinical methods of goniometry and visual estimation require an experienced user and suffer from low inter-rater reliability. More sophisticated techniques such as optical or electromagnetic motion capture exist but are expensive and restricted to a specialised laboratory environment.;Inertial measurement units (IMU), such as those within smartphones and smartwatches, show promise as tools bridge the gap between laboratory and clinical techniques and accurately measure shoulder range of motion during both clinic assessments and in daily life.;This study aims to develop an Android mobile application for both a smartphone and a smartwatch to assess shoulder range of motion. Initial performance characterisation of the inertial sensing capabilities of both a smartwatch and smartphone running the application was conducted against an industrial inclinometer, free-swinging pendulum and custom-built servo-powered gimbal.;An initial validation study comparing the smartwatch application with a universal goniometer for shoulder ROM assessment was conducted with twenty healthy participants. An impaired condition was simulated by applying kinesiology tape across the participants shoulder girdle. Agreement, intra and inter-day reliability were assessed in both the healthy and impaired states.;Both the phone and watch performed with acceptable accuracy and repeatability during static (within ±1.1°) and dynamic conditions where it was strongly correlated to the pendulum and gimbal data (ICC > 0.9). Both devices could perform accurately within optimal responsiveness range of angular velocities compliant with humerus movement during activities of daily living (frequency response of 377°/s and 358°/s for the phone and watch respectively).;The concurrent agreement between the watch and the goniometer was high in both healthy and impaired states (ICC > 0.8) and between measurement days (ICC > 0.8). The mean absolute difference between the watch and the goniometer were within the accepted minimal clinically important difference for shoulder movement (5.11° to 10.58°).;The results show promise for the use of the developed Android application to be used as a goniometry tool for assessment of shoulder ROM. However, the limits of agreement across all the tests fell out with the acceptable margin and further investigation is required to determine validity. Evaluation of validity in clinical impairment patients is also required to assess the feasibility of the use of the application in clinical practice.In patients with shoulder movement impairment, assessing and monitoring shoulder range of motion is important for determining the severity of impairments due to disease or injury and evaluating the effects of interventions. Current clinical methods of goniometry and visual estimation require an experienced user and suffer from low inter-rater reliability. More sophisticated techniques such as optical or electromagnetic motion capture exist but are expensive and restricted to a specialised laboratory environment.;Inertial measurement units (IMU), such as those within smartphones and smartwatches, show promise as tools bridge the gap between laboratory and clinical techniques and accurately measure shoulder range of motion during both clinic assessments and in daily life.;This study aims to develop an Android mobile application for both a smartphone and a smartwatch to assess shoulder range of motion. Initial performance characterisation of the inertial sensing capabilities of both a smartwatch and smartphone running the application was conducted against an industrial inclinometer, free-swinging pendulum and custom-built servo-powered gimbal.;An initial validation study comparing the smartwatch application with a universal goniometer for shoulder ROM assessment was conducted with twenty healthy participants. An impaired condition was simulated by applying kinesiology tape across the participants shoulder girdle. Agreement, intra and inter-day reliability were assessed in both the healthy and impaired states.;Both the phone and watch performed with acceptable accuracy and repeatability during static (within ±1.1°) and dynamic conditions where it was strongly correlated to the pendulum and gimbal data (ICC > 0.9). Both devices could perform accurately within optimal responsiveness range of angular velocities compliant with humerus movement during activities of daily living (frequency response of 377°/s and 358°/s for the phone and watch respectively).;The concurrent agreement between the watch and the goniometer was high in both healthy and impaired states (ICC > 0.8) and between measurement days (ICC > 0.8). The mean absolute difference between the watch and the goniometer were within the accepted minimal clinically important difference for shoulder movement (5.11° to 10.58°).;The results show promise for the use of the developed Android application to be used as a goniometry tool for assessment of shoulder ROM. However, the limits of agreement across all the tests fell out with the acceptable margin and further investigation is required to determine validity. Evaluation of validity in clinical impairment patients is also required to assess the feasibility of the use of the application in clinical practice

Wearable Movement Sensors for Rehabilitation: From Technology to Clinical Practice

This Special Issue shows a range of potential opportunities for the application of wearable movement sensors in motor rehabilitation. However, the papers surely do not cover the whole field of physical behavior monitoring in motor rehabilitation. Most studies in this Special Issue focused on the technical validation of wearable sensors and the development of algorithms. Clinical validation studies, studies applying wearable sensors for the monitoring of physical behavior in daily life conditions, and papers about the implementation of wearable sensors in motor rehabilitation are under-represented in this Special Issue. Studies investigating the usability and feasibility of wearable movement sensors in clinical populations were lacking. We encourage researchers to investigate the usability, acceptance, feasibility, reliability, and clinical validity of wearable sensors in clinical populations to facilitate the application of wearable movement sensors in motor rehabilitation

Development of Wearable Sensors for Body Joint Angle Measurement

This thesis presents the development of three different methods for body joint angle measurement using wearable sensors. Continuous monitoring of patients\u27 movements and activities has recently become one of the active research areas in the field of body sensor network and telehealth monitoring. For many medical and rehabilitation applications, a continuous monitor of the patients\u27 daily activities at home without visiting the hospital is desirable. This type of monitoring is beneficial for the therapists and physicians as it does not require patients\u27 physical presence. Traditionally, measuring the range of motion (ROM) is performed in hospitals by utilizing standard tools such as a goniometer. This method needs to be fulfilled by a physiotherapist in the hospital and requires great deal of overhead. Thus, a remote sensing technique for monitoring the progress of body joint flexion during regular daily life activities becomes very beneficial. The main focus of this thesis is on developing different methods for sensing body joint angle, although we developed some mechanisms for transmitting measurements from patient\u27s side to a remote server at the hospital. The first method for measuring the joint angle- specifically the knee joint- is based on an encoder attached to a brace. The second method is performed by utilizing a wearable cloth with flex-sensors. In the third method, inertial measurement units (IMUs) are employed to measure the desired joint angle. We conducted several experiments to compare the feasibility and accuracy of each method for angle measurement with ground truth measurements. The advantages and disadvantages of each approach are discussed and explained in detail in the assigned section

Wearable inertial sensors and range of motion metrics in physical therapy remote support

Abstract. The practice of physiotherapy diagnoses patient ailments which are often treated by the daily repetition of prescribed physiotherapeutic exercise. The effectiveness of the exercise regime is dependent on regular daily repetition of the regime and the correct execution of the prescribed exercises. Patients often have issues learning unfamiliar exercises and performing the exercise with good technique. This design science research study examines a back squat classifier design to appraise patient exercise regime away from the physiotherapy practice. The scope of the exercise appraisal is limited to one exercise, the back squat. Kinematic data captured with commercial inertial sensors is presented to a small group of physiotherapists to illustrate the potential of the technology to measure range of motion (ROM) for back squat appraisal. Opinions are considered from two fields of physiotherapy, general musculoskeletal and post-operative rehabilitation. While the exercise classifier is considered not suitable for post-operative rehabilitation, the opinions expressed for use in general musculoskeletal physiotherapy are positive. Kinematic data captured with gyroscope sensors in the sagittal plane is analysed with Matlab to develop a method for back squat exercise recognition and appraisal. The artefact, a back squat classifier with appraisal features is constructed from Matlab scripts which are proven to be effective with kinematic data from a novice athlete

Development of techniques for measuring the mobility of knee joints in children with Cerebral Palsy

Cerebral Palsy, commonly referred to as CP, is a neurological disorder that results in loss or impairment of motor function, which affects body movement, muscle control, muscle coordination and balance. In Sweden, about 200 children are diagnosed with Cerebral Palsy every year and the disorder can cause imbalances between the muscles. These imbalances can lead to contractures which is equiva- lent to permanent shortening of muscles and stiffness of joints. This can severely affect the mobility of the child and the quality of life. Today, the only way for physicians or physiotherapists to evaluate the movement of the joints, is during a patient’s short visits to the hospital. The purpose of this project was to develop a device that was able to measure the range of motion of the knee during a longer period of time, which could help customize the child’s rehabilitation. The initial approach was to implement two inertial measurement units (IMUs) and find the angle between the sensors. Different solutions on finding the angle was tested without being able to obtain stable data and the project members chose a new approach. Instead of IMUs, a potentiometer was used and stable data was obtained. A prototype was developed in an iterative and incremental product development process and data was collected during different types of physical exercise. The final prototype was wireless, able to collect data during ordinary life activities and had a battery life of over 30 hours. The data was analyzed and the results were accurate but showed that the prototype probably hindered some of the natural movement of the knee. The developed prototype is a step towards being able to measure the knee range of motion during a longer period of time, and could be a tool for physicians and other medical staff when evaluating and rehabilitating children with CP.Utveckling av mätteknik för mätning av rörligheten i knäleder hos barn med Cerebral pares Cerebral pares (CP) är en neurologisk störning som kan leda till förlust eller nedsättning av de motoriska funktioner som påverkar kroppens rörelser, muskelkontroll, koordination och balans. CP kan orsaka obalanser mellan musklerna som kan leda till kontrakturer. Kontrakturer innebär att musklerna förkortas permanent och styvheten i lederna ökar. Muskelförkortning och styva leder kan drastiskt påverka barnets rörlighet och därmed även livskvaliteten. I Sverige diagnostiseras cirka 200 barn varje år med CP och i dagsläget är det enda sättet för läkaren eller fysioterapeuten att utvärdera barnens rörelsefunktion under kortare besök på sjukhuset, 1-2 gånger per år. Därför var syftet med detta projekt att utveckla en prototyp som kunde mäta knäets ledrörlighet under en längre period

Optical goniometer device for continuous monitoring of the knee movement in physiotherapy application

Knee joint is the most crucial among the lower limbs joints due to its exposed location and its major role which carries the entire burden of the body practically our entire life. Hence, by being able to measure the knee joint angle accurately during continuous movement, allows the physiotherapist to detect knee joint damage at early stages before it turns into an injury or permanent scar tissue. Due to the limited number of continuous monitoring devices applicable for diagnosis and treatment stage of the knee, most physicians opted for X-ray and magnetic resonance imaging (MRI) technologies to have some insight on the knee issue before suitable treatment can be recommended. Aside from being expensive for general use of MRI, X-ray on the other hand can cause short-term side effects due to radiation exposure. Knee joint angle measurement devices technologies include but are not limited to the implementation of accelerometer, electrogoniometer, torsiometer, acoustic, visual sensory, and optic fibre. There are many limitations to these technologies that require improvements before they can become clinically applicable such as accuracy issues, limited range of motion measurement, and inability to monitor continuous movement measurement of the knee joint, which have been discussed thoroughly in this research. The need for technologies with higher accuracy, reliability, able to measure the full knee range of motion, applicable for continuous motion measurement and lower cost have always been a crucial factor. The use of optical based devices provides significant contribution in this area due to their advantages such as immunity to electromagnetic interference, lightweight and possibly small sensor setup. However, the application of intensity-based optical fibre sensor for human joint motion detection resulted in limited detection angle, where most sensor are not able to detect angle variation of more than 90ᵒ. To improve this limitation, an optical sensor approach with mechanical-assisted components assembly that translates angular movement to linear movement was developed. The light detection on the photodiode array sensor at different pixels is analysed to represent the angle movement of the knee. The sensor is securely attached to a medical standard knee brace tool to ensure firm sensor placement on the knee area. Based on current study, the proposed optical sensor has a range of motion between 0 to 160ᵒ, with 0.08ᵒ resolution, has a 210.5 sampling rate per second, which allows it to present and record a real time graphical output to demonstrate the knee joint activity performance. Moreover, the proposed device was able to give an excellent internal consistency obtained by Cronbach’s Alpha analysis of 0.967, and has 98.044% correlation with the gold standard goniometer

Objective assessment of movement disabilities using wearable sensors

The research presents a series of comprehensive analyses based on inertial measurements obtained from wearable sensors to quantitatively describe and assess human kinematic performance in certain tasks that are most related to daily life activities. This is not only a direct application of human movement analysis but also very pivotal in assessing the progression of patients undergoing rehabilitation services. Moreover, the detailed analysis will provide clinicians with greater insights to capture movement disorders and unique ataxic features regarding axial abnormalities which are not directly observed by the clinicians