Developing a method for quantifying hip joint angles and moments during walking using neural networks and wearables

Quantifying hip angles/moments during gait is critical for improving hip pathology diagnostic and treatment methods. Recent work has validated approaches combining wearables with artificial neural networks (ANNs) for cheaper, portable hip joint angle/moment computation. This study developed a Wearable-ANN approach for calculating hip joint angles/moments during walking in the sagittal/frontal planes with data from 17 healthy subjects, leveraging one shin-mounted inertial measurement unit (IMU) and a force-measuring insole for data capture. Compared to the benchmark approach, a two hidden layer ANN (n = 5 nodes per layer) achieved an average rRMSE = 15% and R2=0.85 across outputs, subjects and training rounds

Master of Science

thesisGait analysis is an important tool for diagnosing a wide variety of disorders, with its increasingly accepted benefits culminating in the widespread adoption of motion analysis laboratories. A modern analysis laboratory consists of a multicamera marker tracking system for 3D reconstruction of kinematics and multiple high-fidelity load transducers to determine ground reaction force and enable inverse-dynamics for biomechanics. There is a need for an alternative motion analysis system which does not require a fixed laboratory setting and is lower in cost; freeing the motion capture from the laboratory and reducing the technology costs would enable long-term, home-based, natural monitoring of subjects. This thesis describes two contributions to the end goal of an inexpensive, mobile, insole-based motion analysis laboratory. First is the application of an inertialmeasurement-unit calibration routine and zero-velocity-update algorithm to improve position and orientation tracking. Second is the development, from basic sensor to prototype, of an insole capable of measuring 3 degree-of-freedom ground reaction force. These contributions represent a proof-of-concept that quantitative gait analysis, complete with dynamics, is possible with an insole-based system

Moving On:Measuring Movement Remotely after Stroke

Most persons with stroke suffer from motor impairment, which restricts mobility on one side, and affects their independence in daily life activities. Measuring recovery is needed to develop individualized therapies. However, commonly used clinical outcomes suffer from low resolution and subjectivity. Therefore, objective biomechanical metrics should be identified to measure movement quality. However, non-portable laboratory setups are required in order to measure these metrics accurately. Alternatively, minimal wearable systems can be developed to simplify measurements performed at clinic or home to monitor recovery. Thus, the goal of the thesis was ‘To identify metrics that reflect movement quality of upper and lower extremities after stroke and develop wearable minimal systems for tracking the proposed metrics’. Section Upper Extremity First, we systematically reviewed literature ( Chapter II ) to identify metrics used to measure reaching recovery longitudinally post-stroke. Although several metrics were found, it was not clear how they differentiated recovery from compensation strategies. Future studies must address this gap in order to optimize stroke therapy. Next, we assessed a ‘valid’ measure for smoothness of upper paretic limb reaching ( Chapter III ), as this was commonly used to measure movement quality. After a systematic review and simulation analyses, we found that reaching smoothness is best measured using spectral arc length. The studies in this section offer us a better understanding of movement recovery in the upper extremity post-stroke. Section Lower Extremity Although metrics that reflect gait recovery are yet to be identified, in this section we focused on developing minimal solutions to measure gait quality. First, we showed the feasibility of 1D pressure insoles as a lightweight alternative for measuring 3D Ground Reaction Forces (GRF) ( Chapter IV ). In the following chapters, we developed a minimal system; the Portable Gait Lab (PGL) using only three Inertial Measurement Units (IMUs) (one per foot and one on the pelvis). We explored the Centroidal Moment Pivot (CMP) point ( Chapter V ) as a biomechanical constraint that can help with the reduction in sensors. Then, we showed the feasibility of the PGL to track 3D GRF ( Chapters VI-VII ) and relative foot and CoM kinematics ( Chapter VIII-IX ) during variable overground walking by healthy participants. Finally, we performed a limited validation study in persons with chronic stroke ( Chapter X ). This thesis offers knowledge and tools which can help clinicians and researchers understand movement quality and thereby develop individualized therapies post-stroke

Body mass index and its effect on plantar pressure in overweight and obese adults

The proportion of overweight or obese adults is creating a growing problem throughout the world. Overweight and obesity have a significant influence on gait, and often cause difficulty. There is evidence to suggest that being overweight or obese places adults at a greater risk of developing foot complications such as osteoarthritis, tendonitis, plantar fasciitis, and foot ulcers. Increasingly, pressure ulcers have become a serious health problem. The purpose of this research is to investigate the effect of body weight on the feet, and to investigate the use of simulated body mass to study the effect of variable body mass on the foot plantar in adults aged 24 to 50 years of age while walking at a self-selected pace. A series of studies were undertaken to achieve the above purpose. The research involved: 1) assessing dynamic foot plantar pressure characteristics in adults who are normal weight, overweight or obese; 2) studying the gait impact of increased simulated body weight (SBW); and 3) evaluating the spatial relationship between the trace of the centroid of the area of contact with heel strike, midstance, and toe-off phases for the SBW groups. F-Scan in-shoe systems were utilised to gather the foot pressure data. The first study sought to investigate the effect of different body mass index (BMI) levels on plantar pressure distribution during walking, collection in fifteen voluntary participants were recruited. The BMI participants were divided into three groups (healthy, overweight and obese). The foot was divided into ten regions: heel (H), midfoot (MF), first metatarsal head (1MH), second metatarsal head (2MH), third metatarsal head (3MH), fourth metatarsal head (4MH), fifth metatarsal head (5MH), hallux (1stT), second toe (2ndT), and third to fifth toes (3rd-5thT). For each region, the following parameters were calculated: force (F), contact area (CA), contact pressure (CP), pressure time integral (PTI) and peak pressure (PP). The mean of the three repetitions of each subject was computed, and statistical procedures were performed with these mean ± standard deviation (SD) values. This study showed that the obese group had higher plantar pressure parameter values compared to the other two groups (overweight and healthy) for the ten different foot regions. The study observed significant changes in the parameters in the H and MHs (e.g. 2MH and 3MH) foot regions. The forefoot appears to be more sensitive to weight-related pressure under the foot than the rearfoot. Findings from this study indicate that being overweight or obese increases foot pressure measures, even for individuals with similar body features. Higher BMI values correlate with a higher load on the foot during walking in males. These findings have implications for pain and discomfort in the lower extremity in the obese while participating in activities of daily living such as walking. The second study investigated the effect of the research methodology involving the simulation of body weight (SBW) with additional weight, adding 10, 20, 30 kg to each participant’s body weight on plantar pressures. The sample comprised 31 adult males; each subject walked four times. The first walk was without any external weight (NBW, 0 kg), the second walk was with a weight of 10 kg, the third walk was with a weight of 20 kg and the last walk with a weight of 30 kg in the vest. The foot was divided into ten regions and for each region, the parameters were calculated the same way as the first study. At the end of this study it should be noted that SBW groups subjected to load have shown changes in foot plantar measure values compared to the NBW group. Most of the differences were found under H, MHs, 1stT and MF regions in the most clinically relevant parameters in SBW groups compared to the control group; the SBW groups showed higher values of plantar pressure. The results of the ICC showed a generally good to an excellent level of reliability, the quality of which was dependent on the regions of the foot and the variables investigated with SBW loads. This experiment pointed out that an insole pressure system is a reliable tool for evaluating foot plantar forces and pressures throughout the walk. The plantar pressure measures can be used in relative assessments, as the measures of repeatability are favourable for the measures and foot zones generally utilised in the study of people with clinical problems like neuropathic diabetics. In the final study, associations were investigated of the centroid (coordinates x-axis and y-axis) of the area of contact captured between normal (NBW) and simulated body weight (SBW) changes. The same 31 adult males who enrolled with the SBW tests were used to collect the centroid of the area of contact with the surface. This was located by calculating the geometric centre of a set of cloud points having the lowest z coordinate value. In this part, a foot pressure sensing insole was used to calculate the moment of heel strike, midstance and toe-off phases. Data were analysed descriptively (mean ± SD only). The outcome of this study, relating to specific individual characteristics of the centroid trace of the plantar contact area was compared with the heel strike, midstance, and toe-off phases for the SBW group with the NSBW group. X-axis and y-axis coordinates in the heel strike, midstance and toe-off phases under SBW with 30, 20, 10 kg had higher mean values compared to NSW. The x-axis and y-axis coordinates had mean values of 11.76, 9.68, and 7.76 mm; while the y-axis coordinates had mean values of 11.96, 9.89, and 8.18 mm. Moreover, x-axis and y-axis coordinates were assessed in the midstance phase under SBW with 30, 20, 10 kg with means of 6.59, 5.48, and 4.50 mm; while the y-axis coordinates had mean values of 6.38, 5.41, and 4.41 mm. In addition, x-axis and y-axis coordinates were assessed in the toe-off phase under SBW (30, 20, 10 kg) with mean values of 11.56, 9.67, and 7.97 mm; while the y-axis coordinates had mean values of 11.51, 9.39, 8.02 mm, respectively. X-axis and y-axis coordinates had mean values in relation to NBW in three phases: heel strike of 5.47 and 6.15; midstance of 2.99 and 3.05; and toe-off of 6.04 and 5.82, respectively. The x-locate and y-locate change can be calculate the change in rotation of the ankle joint. As the data was normalised according to the total time taken for the loading phase of the gait, the y-locational change was due partly to the extra weight, which could increase the time of lifting the foot. Therefore, the results showed that the x-locate and y-locate change can help to calculate the change in the rotation of the ankle joint. The project has shown that it is possible to demonstrate that obese people will, throughout their lives, adopt ways to effectively execute a particular activity. This finding provides a foundation for future clinical trials which could assist in preventing foot complications and could assist in the design of appropriate interventions to promote healthy outcomes for these adults. The simulated body weight resulted in a variation in plantar pressure distribution. Because the human foot adapts itself to any simulated condition, knowledge of the variation of pressure distributions of both feet can provide input for suitable guidelines for biomedical engineers. To promote the prevention of likely injury to the feet of overweight and obese people, the results of this study demonstrate the need to develop strategies which could include the building of an insole (orthosis) that absorbs foot plantar pressure

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

Fusion of wearable and visual sensors for human motion analysis

Human motion analysis is concerned with the study of human activity recognition, human motion tracking, and the analysis of human biomechanics. Human motion analysis has applications within areas of entertainment, sports, and healthcare. For example, activity recognition, which aims to understand and identify different tasks from motion can be applied to create records of staff activity in the operating theatre at a hospital; motion tracking is already employed in some games to provide an improved user interaction experience and can be used to study how medical staff interact in the operating theatre; and human biomechanics, which is the study of the structure and function of the human body, can be used to better understand athlete performance, pathologies in certain patients, and assess the surgical skill of medical staff. As health services strive to improve the quality of patient care and meet the growing demands required to care for expanding populations around the world, solutions that can improve patient care, diagnosis of pathology, and the monitoring and training of medical staff are necessary. Surgical workflow analysis, for example, aims to assess and optimise surgical protocols in the operating theatre by evaluating the tasks that staff perform and measurable outcomes. Human motion analysis methods can be used to quantify the activities and performance of staff for surgical workflow analysis; however, a number of challenges must be overcome before routine motion capture of staff in an operating theatre becomes feasible. Current commercial human motion capture technologies have demonstrated that they are capable of acquiring human movement with sub-centimetre accuracy; however, the complicated setup procedures, size, and embodiment of current systems make them cumbersome and unsuited for routine deployment within an operating theatre. Recent advances in pervasive sensing have resulted in camera systems that can detect and analyse human motion, and small wear- able sensors that can measure a variety of parameters from the human body, such as heart rate, fatigue, balance, and motion. The work in this thesis investigates different methods that enable human motion to be more easily, reliably, and accurately captured through ambient and wearable sensor technologies to address some of the main challenges that have limited the use of motion capture technologies in certain areas of study. Sensor embodiment and accuracy of activity recognition is one of the challenges that affect the adoption of wearable devices for monitoring human activity. Using a single inertial sensor, which captures the movement of the subject, a variety of motion characteristics can be measured. For patients, wearable inertial sensors can be used in long-term activity monitoring to better understand the condition of the patient and potentially identify deviations from normal activity. For medical staff, inertial sensors can be used to capture tasks being performed for automated workflow analysis, which is useful for staff training, optimisation of existing processes, and early indications of complications within clinical procedures. Feature extraction and classification methods are introduced in thesis that demonstrate motion classification accuracies of over 90% for five different classes of walking motion using a single ear-worn sensor. To capture human body posture, current capture systems generally require a large number of sensors or reflective reference markers to be worn on the body, which presents a challenge for many applications, such as monitoring human motion in the operating theatre, as they may restrict natural movements and make setup complex and time consuming. To address this, a method is proposed, which uses a regression method to estimate motion using a subset of fewer wearable inertial sensors. This method is demonstrated using three sensors on the upper body and is shown to achieve mean estimation accuracies as low as 1.6cm, 1.1cm, and 1.4cm for the hand, elbow, and shoulders, respectively, when compared with the gold standard optical motion capture system. Using a subset of three sensors, mean errors for hand position reach 15.5cm. Unlike human motion capture systems that rely on vision and reflective reference point markers, commonly known as marker-based optical motion capture, wearable inertial sensors are prone to inaccuracies resulting from an accumulation of inaccurate measurements, which becomes increasingly prevalent over time. Two methods are introduced in this thesis, which aim to solve this challenge using visual rectification of the assumed state of the subject. Using a ceiling-mounted camera, a human detection and human motion tracking method is introduced to improve the average mean accuracy of tracking to within 5.8cm in a laboratory of 3m × 5m. To improve the accuracy of capturing the position of body parts and posture for human biomechanics, a camera is also utilised to track the body part movements and provide visual rectification of human pose estimates from inertial sensing. For most subjects, deviations of less than 10% from the ground truth are achieved for hand positions, which exhibit the greatest error, and the occurrence of sources of other common visual and inertial estimation errors, such as measurement noise, visual occlusion, and sensor calibration are shown to be reduced.Open Acces

Evaluating footwear “in the wild”: Examining wrap and lace trail shoe closures during trail running

Trail running participation has grown over the last two decades. As a result, there have been an increasing number of studies examining the sport. Despite these increases, there is a lack of understanding regarding the effects of footwear on trail running biomechanics in ecologically valid conditions. The purpose of our study was to evaluate how a Wrap vs. Lace closure (on the same shoe) impacts running biomechanics on a trail. Thirty subjects ran a trail loop in each shoe while wearing a global positioning system (GPS) watch, heart rate monitor, inertial measurement units (IMUs), and plantar pressure insoles. The Wrap closure reduced peak foot eversion velocity (measured via IMU), which has been associated with fit. The Wrap closure also increased heel contact area, which is also associated with fit. This increase may be associated with the subjective preference for the Wrap. Lastly, runners had a small but significant increase in running speed in the Wrap shoe with no differences in heart rate nor subjective exertion. In total, the Wrap closure fit better than the Lace closure on a variety of terrain. This study demonstrates the feasibility of detecting meaningful biomechanical differences between footwear features in the wild using statistical tools and study design. Evaluating footwear in ecologically valid environments often creates additional variance in the data. This variance should not be treated as noise; instead, it is critical to capture this additional variance and challenges of ecologically valid terrain if we hope to use biomechanics to impact the development of new products

Low-Cost Sensors and Biological Signals

Many sensors are currently available at prices lower than USD 100 and cover a wide range of biological signals: motion, muscle activity, heart rate, etc. Such low-cost sensors have metrological features allowing them to be used in everyday life and clinical applications, where gold-standard material is both too expensive and time-consuming to be used. The selected papers present current applications of low-cost sensors in domains such as physiotherapy, rehabilitation, and affective technologies. The results cover various aspects of low-cost sensor technology from hardware design to software optimization