Inertial sensor-based knee flexion/extension angle estimation

A new method for estimating knee joint flexion/extension angles from segment acceleration and angular velocity data is described. The approach uses a combination of Kalman filters and biomechanical constraints based on anatomical knowledge. In contrast to many recently published methods, the proposed approach does not make use of the earth’s magnetic field and hence is insensitive to the complex field distortions commonly found in modern buildings. The method was validated experimentally by calculating knee angle from measurements taken from two IMUs placed on adjacent body segments. In contrast to many previous studies which have validated their approach during relatively slow activities or over short durations, the performance of the algorithm was evaluated during both walking and running over 5 minute periods. Seven healthy subjects were tested at various speeds from 1 to 5 miles/hour. Errors were estimated by comparing the results against data obtained simultaneously from a 10 camera motion tracking system (Qualysis). The average measurement error ranged from 0.7 degrees for slow walking (1 mph) to 3.4 degrees for running (5mph). The joint constraint used in the IMU analysis was derived from the Qualysis data. Limitations of the method, its clinical application and its possible extension are discussed

Wearable Sensors and Smart Devices to Monitor Rehabilitation Parameters and Sports Performance: An Overview

A quantitative evaluation of kinetic parameters, the joint’s range of motion, heart rate, and breathing rate, can be employed in sports performance tracking and rehabilitation monitoring following injuries or surgical operations. However, many of the current detection systems are expensive and designed for clinical use, requiring the presence of a physician and medical staff to assist users in the device’s positioning and measurements. The goal of wearable sensors is to overcome the limitations of current devices, enabling the acquisition of a user’s vital signs directly from the body in an accurate and non–invasive way. In sports activities, wearable sensors allow athletes to monitor performance and body movements objectively, going beyond the coach’s subjective evaluation limits. The main goal of this review paper is to provide a comprehensive overview of wearable technologies and sensing systems to detect and monitor the physiological parameters of patients during post–operative rehabilitation and athletes’ training, and to present evidence that supports the efficacy of this technology for healthcare applications. First, a classification of the human physiological parameters acquired from the human body by sensors attached to sensitive skin locations or worn as a part of garments is introduced, carrying important feedback on the user’s health status. Then, a detailed description of the electromechanical transduction mechanisms allows a comparison of the technologies used in wearable applications to monitor sports and rehabilitation activities. This paves the way for an analysis of wearable technologies, providing a comprehensive comparison of the current state of the art of available sensors and systems. Comparative and statistical analyses are provided to point out useful insights for defining the best technologies and solutions for monitoring body movements. Lastly, the presented review is compared with similar ones reported in the literature to highlight its strengths and novelties

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

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

MEMS Accelerometers

Micro-electro-mechanical system (MEMS) devices are widely used for inertia, pressure, and ultrasound sensing applications. Research on integrated MEMS technology has undergone extensive development driven by the requirements of a compact footprint, low cost, and increased functionality. Accelerometers are among the most widely used sensors implemented in MEMS technology. MEMS accelerometers are showing a growing presence in almost all industries ranging from automotive to medical. A traditional MEMS accelerometer employs a proof mass suspended to springs, which displaces in response to an external acceleration. A single proof mass can be used for one- or multi-axis sensing. A variety of transduction mechanisms have been used to detect the displacement. They include capacitive, piezoelectric, thermal, tunneling, and optical mechanisms. Capacitive accelerometers are widely used due to their DC measurement interface, thermal stability, reliability, and low cost. However, they are sensitive to electromagnetic field interferences and have poor performance for high-end applications (e.g., precise attitude control for the satellite). Over the past three decades, steady progress has been made in the area of optical accelerometers for high-performance and high-sensitivity applications but several challenges are still to be tackled by researchers and engineers to fully realize opto-mechanical accelerometers, such as chip-scale integration, scaling, low bandwidth, etc

Drift Reduction for Inertial Sensor Based Orientation and Position Estimation in the Presence of High Dynamic Variability During Competitive Skiing and Daily-Life Walking

Nowadays inertial sensors are extensively used for gait analysis. They can be used to perform temporal event detection (i.e. step detection) and to estimate the orientation of the feet and other body segments to determine walking speed and distance. Usually, orientation is estimated from integration of the measured angular velocity. Prior to integration of measured acceleration to obtain speed, the gravity component has to be estimated and removed. During each integration small measurement errors accumulate and result in so-called drift. Since the first uses of inertial sensors for gait analysis methods have been presented to model, estimate and remove the drift. The proposed methods worked well for relatively slow movements and movements taking place in the sagittal plane. Many methods also relied on periodically occurring static phases such as the stance phase during walking to correct the drift. Inertial sensors could also be used to track higher dynamic movements, for example in sports. Potential applications focus on two aspects: performance analysis and injury prevention. To better explain and predict performance, in-field measurements to assess the coordination, kinematics, and dynamics are key. While traditional movement analysis (e.g. video analysis) can answer most of the questions related to both performance and injury, they are cumbersome and complex to use in-field. Inertial sensors, however, are perfectly suited since they allow to measure the movement in any environment and are not restricted to certain capture volumes. Nevertheless, most sports have very high movement dynamics (e.g. fast direction changes, high speeds) and are therefore challenging for computing reliable estimates of orientation, speed and position. The inertial measurements are compromised by noise and movements oftentimes don't provide static or slow phases used in gait analysis for drift correction. Therefore, the present thesis aimed to propose and validate new methods to model, estimate and remove drift in sports and for movements taking place outdoors in uncontrolled environments. Three different strategies were proposed to measure the movement of classical cross-country skiing and ski mountaineering, alpine ski racing, and outdoor walking over several kilometres. For each activity specific biomechanical constraints and movement dynamics were exploited. The proposed methods rely only on inertial sensors and magnetometers and are able to provide orientation, speed, and position information with an accuracy and precision close to existing gold standards. The most complete system was designed in alpine ski racing, probably one of the most challenging sports for movement analysis. Extreme vibrations, high speeds of over 120 km/h and a timing resolution below 0.01 seconds require maximum accuracy and precision. The athlete's posture and the kinematics of his centre of mass both in a relative athlete-centred frame and in a global Earth-fixed frame could be obtained with high accuracy and precision. Where 3D video analysis requires a very complex experimental setup and takes several hours of post processing to analyse a single turn of a skier, the proposed system allows to measure multiple athletes and complete runs within minutes. Thus, new experimental designs to assess performance and injury risk in alpine ski racing became feasible, greatly helping to gain further knowledge about this highly complex and risky sport

Promoting a healthy ageing workforce: use of Inertial Measurement Units to monitor potentially harmful trunk posture under actual working conditions

Musculoskeletal disorders, particularly those involving the low back, represent a major health concern for workers, and originate significant consequences for the socio-economic system. As the average age of the population is gradually (yet steadily) increasing, such phenomenon directly reflects on labor market raising the need to create the optimal conditions for jobs which must be sustainable for the entire working life of an individual, while constantly ensuring good health and quality of life. In this context, prevention and management of low back disorders (LBDs) should be effective starting from the working environment. To this purpose, quantitative, reliable and accurate tools are needed to assess the main parameters associated to the biomechanical risk. In the last decade, the technology of wearable devices has made available several options that have been proven suitable to monitor the physical engagement of individuals while they perform manual or office working tasks. In particular, the use of miniaturized Inertial Measurement Units (IMUs) which has been already tested for ergonomic applications with encouraging results, could strongly facilitate the data collection process, being less time- and resources-consuming with respect to direct or video observations of the working tasks. Based on these considerations, this research intends to propose a simplified measurement setup based on the use of a single IMUs to assess trunk flexion exposure, during actual shifts, in occupations characterized by significant biomechanical risk. Here, it will be demonstrated that such approach is feasible to monitor large groups of workers at the same time and for a representative duration which can be extended, in principle, to the entire work shift without perceivable discomfort for the worker or alterations of the performed task. Obtained data, which is easy to interpret, can be effectively employed to provide feedback to workers thus improving their working techniques from the point of view of safety. They can also be useful to ergonomists or production engineers regarding potential risks associated with specific tasks, thus supporting decisions or allowing a better planning of actions needed to improve the interaction of the individual with the working environment

Thermal and Visual Imaging and Accelerometry Developments to Assist with Arthritis Diagnosis

Juvenile Idiopathic Arthritis (JIA) is a disease that causes pain and inflammation in the joints of children. Its early diagnosis is important to avoid damage to the joints. Joint warmth, redness and movement restriction may be indicators of active arthritis hence accurate objective means to measure temperature, colour and range of movement (ROM) at the joint may assist diagnosis. In this study, three techniques with a potential to assist clinicians in diagnosing JIA were developed. These were based on high-resolution thermal imaging (HRTI), visual imaging and accelerometry. A detailed correlation analysis was performed between the developed methods and the consultant's clinical assessment of JIA diagnosis. Twenty-two patients (age: mean=10.6 years, SD = 2 years) with JIA diagnosis were recruited. 18 participated in the thermal/visual imaging study only, 2 in the accelerometry study only and 2 in both thermal/visual imaging and accelerometry studies. Thermal and visual images of the front and back of the knees and ankles of 20 patients were studied. All ethical approvals from Sheffield Hallam University and the National Health Service (NHS) were duly obtained before commencing the study. The thermal/visual imaging study involved developing image processing techniques to accurately identify and segment the regions of interest (ROIs). A tracking algorithm to accurately locate the ROIs was also implemented. An accelerometry system that is capable of recording movements from 4 channels was developed and its signals were processed by frequency spectrum analysis, short-time Fourier transform and wavelet packet analysis. The thermal imaging results showed a combined 71% correlation (for the front of knees and ankles) with clinical assessment. It may be possible that patients whom their arthritic joint was cooler than their healthy joints may have relied on their healthy leg more extensively for mobility (due to the pain on the arthritic leg) thus increasing its joints temperature. It was also found that JIA may affect the skin colour with a combined 42% correlation between the knees and ankles. The accelerometry results showed a 75% correlation with clinical assessment. The study for the first time brought together the three techniques of thermal imaging, visual imaging and accelerometry to assist with JIA diagnosis. The study demonstrated that the developed techniques have potential in assisting clinicians with JIA diagnosis. Improvements in timely diagnosis allow more effective treatment and can reduce the likelihood of joint damage in rheumatoid arthritis