Master of Science

thesisAbnormal gait caused by stroke or other pathological reasons can greatly impact the life of an individual. Being able to measure and analyze that gait is often critical for rehabilitation. Motion analysis labs and many current methods of gait analysis are expensive and inaccessible to most individuals. The low cost, wearable, and wireless insole-based gait analysis system in this study provides kinetic measurements of gait by using low cost force sensitive resistors. This thesis describes the design and fabrication of two insoles and their evaluation with 10 control subjects and eight hemiplegic stroke subjects. The first insole used 32 force sensitive resistors and was used to determine the ideal locations of 12 sensors in the second insole. Linear regression was used on training data for each subject testing the second insole to determine ground reaction force, ankle dorsiflexion / plantarflexion moment, knee flexion / extension moment, and knee abduction / adduction moment. Comparison with data collected simultaneously from a clinical motion analysis laboratory demonstrated that the insole results for ground reaction force and ankle moment were highly correlated (all > 0.95) for all subjects, while the two knee moments were less strongly correlated (generally > 0.80). This provides a means of cost effective and efficient healthcare delivery of mobile gait analysis that can be used anywhere from large clinics to an individual's home. The two insoles also provide the means for further testing of force sensitive resistors in different applications

A Hidden Markov Model Based Detecting Solution for Detecting the Situation of Balance During Unsupported Standing Using the Electromyography of Ankle Muscles

Quiet Standing; Hidden Markov Model; Electromyography; Dynamic Balance.: In this study, three detecting approaches have been proposed and evaluated for online detection of balance situations during quiet standing. The applied methods were based on electromyography of the gastrocnemius muscles adopting the hidden Markov models.Methods: The levels of postural stability during quiet standing were regarded as the hidden states of the Markov models while the zones in which the center of pressure lies within determines the level of stability. The Markov models were trained by using the well-known Baum-Welch algorithm. The performance of a single hidden Markov model, the multiple hidden Markov model, and the multiple hidden Markov model alongside an adaptive neuro-fuzzy inference system (ANFIS), were compared as three different detecting methods.Results: The obtained results show the better and more promising performance of the method designed based on a combination of the hidden Markov models and optimized neuro-fuzzy system.Conclusion: According to the results, using the combined detecting method yielded promising results

The Development of an assistive chair for elderly with sit to stand problems

A thesis submitted to the University of Bedfordshire in partial fulfilment of the requirements for the degree of Doctor of PhilosophyStanding up from a seated position, known as sit-to-stand (STS) movement, is one of the most frequently performed activities of daily living (ADLs). However, the aging generation are often encountered with STS issues owning to their declined motor functions and sensory capacity for postural control. The motivated is rooted from the contemporary market available STS assistive devices that are lack of genuine interaction with elderly users. Prior to the software implementation, the robot chair platform with integrated sensing footmat is developed with STS biomechanical concerns for the elderly. The work has its main emphasis on recognising the personalised behavioural patterns from the elderly users’ STS movements, namely the STS intentions and personalised STS feature prediction. The former is known as intention recognition while the latter is defined as assistance prediction, both achieved by innovative machine learning techniques. The proposed intention recognition performs well in multiple subjects scenarios with different postures involved thanks to its competence of handling these uncertainties. To the provision of providing the assistance needed by the elderly user, a time series prediction model is presented, aiming to configure the personalised ground reaction force (GRF) curve over time which suggests successful movement. This enables the computation of deficits between the predicted oncoming GRF curve and the personalised one. A multiple steps ahead prediction into the future is also implemented so that the completion time of actuation in reality is taken into account

Effect of 8-week exerciseon improving the static and dynamic balance of supinated foot

Background: the supinated foot is one of the lower limb abnormalities that is associated with navicular drop and may be affected by leg muscles. The aim of this study was to investigate the effects of 8-week corrective exercises to improve static and dynamic balance of supinated foot.Materials and methods: The current research is a quasi-experimental study, in which twenty 18-25 male subjects that all suffer supinated leg were chosen purposefully into two groups (10) of experimental and control. Before the training program of supinated legs of navicular drop test subjects, static balance and dynamic balance was measured with a force platform. The experimental group carried out exercises program for 8 weeks with a frequency of three times a week on the area of weak muscles and stretched legs, and the control group were doing their usual activities. After 8 weeks of corrective exercises, static and dynamic balance and supinated leg were measured again. To analyze the data, independent t-test for changes between the group and dependent t-test for within-group changes were used.Findings: The results showed a significant increase in static balance (shifting the center of pressure, p = 0.011), dynamic balance (time to stabilization in the lateral direction, p = 0.008) as well as supinated leg (p = 0.00)between pre-test and post-test experimental group. However, no significant differences in dynamic balance in the anterior-posterior direction (p = 0.2) in the experimental group were observed. In the control group variables during the study period, no significant difference was observed.Conclusion: Using corrective exercises presented in this study, the static and dynamic balance level and navicular drop could be improved, and supinated foot deformity was corrected.Keywords: corrective exercises, static balance, dynamic balance, supinated foo

Design of a Lightweight, Cost Effective Thimble-Like Sensor for Haptic Applications Based on Contact Force Sensors

This paper describes the design and calibration of a thimble that measures the forces applied by a user during manipulation of virtual and real objects. Haptic devices benefit from force measurement capabilities at their end-point. However, the heavy weight and cost of force sensors prevent their widespread incorporation in these applications. The design of a lightweight, user-adaptable, and cost-effective thimble with four contact force sensors is described in this paper. The sensors are calibrated before being placed in the thimble to provide normal and tangential forces. Normal forces are exerted directly by the fingertip and thus can be properly measured. Tangential forces are estimated by sensors strategically placed in the thimble sides. Two applications are provided in order to facilitate an evaluation of sensorized thimble performance. These applications focus on: (i) force signal edge detection, which determines task segmentation of virtual object manipulation, and (ii) the development of complex object manipulation models, wherein the mechanical features of a real object are obtained and these features are then reproduced for training by means of virtual object manipulation

Design of a Wearable Balance Control Indicator

Each year, one in three elderly fall. Studies show that many factors contribute to an elderly person\u27s risk of falling, but if the factors causing imbalance are improved, a person\u27s risk of falling may be reduced. A device that detects and alerts the user of an off-balance situation before the fall occurs could identify a specific need for improved balance control. This MQP describes the design, testing, and verification of a prototype wearable device that is worn on the right hip during the sit-to-stand activity (STS) to detect and notify the user of an unbalanced STS. By signaling an off-balance situation during STS, our device notifies the user of poor balance control and identifies the need for balance control improvement

A distributive approach to tactile sensing for application to human movement

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonThis thesis investigates on clinical applicability of a novel sensing technology in the areas of postural steadiness and stroke assessment. The mechanically simple Distributive Tactile Sensing approach is applied to extract motion information from flexible surfaces to identify parameters and disorders of human movement in real time. The thesis reports on the design, implementation and testing of smart platform devices which are developed for discrimination applications through the use of linear and non-linear data interpretation techniques and neural networks for pattern recognition. In the thesis mathematical models of elastic plates, based on finite element and finite difference methods, are developed and described. The models are used to identify constructive parameters of sensing devices by investigating sensitivity and accuracy of Distributive Tactile Sensing surfaces. Two experimental devices have been constructed for the investigation. These are a sensing floor platform for standing applications and a sensing chair for sitting applications. Using a linear approach, the sensing floor platform is developed to detect centre of pressure, an important parameter widely used in the assessment of postural steadiness. It is demonstrated that the locus of centre of pressure can be determined with an average deviation of 1.05mm from that of a commercialised force platform in a balance application test conducted with five healthy volunteers. This amounts to 0.4% of the sensor range. The sensing chair used neural networks for pattern recognition, to identify the level of motor impairment in people with stroke through performing functional reaching task while sitting. The clinical studies with six real stroke survivors have shown the robustness of the sensing technique to deal with a range of possible motion in the reaching task investigated. The work of this thesis demonstrates that the novel Distributive Tactile Sensing approach is suited to clinical and home applications as screening and rehabilitation systems. Mechanical simplicity is a merit of the approach and has potential to lead to versatile low-cost units

Wearables for Movement Analysis in Healthcare

Quantitative movement analysis is widely used in clinical practice and research to investigate movement disorders objectively and in a complete way. Conventionally, body segment kinematic and kinetic parameters are measured in gait laboratories using marker-based optoelectronic systems, force plates, and electromyographic systems. Although movement analyses are considered accurate, the availability of specific laboratories, high costs, and dependency on trained users sometimes limit its use in clinical practice. A variety of compact wearable sensors are available today and have allowed researchers and clinicians to pursue applications in which individuals are monitored in their homes and in community settings within different fields of study, such movement analysis. Wearable sensors may thus contribute to the implementation of quantitative movement analyses even during out-patient use to reduce evaluation times and to provide objective, quantifiable data on the patients’ capabilities, unobtrusively and continuously, for clinical purposes