Recognizing Different Foot Deformities Using FSR Sensors by Static Classification of Neural Networks

تُعَدُّ أنظمة النعال الحسّاسة للحركة تقنية واعدة للعديد من التطبيقات في الرعاية الصحية والرياضة. حيث يمكن أن توفّر هذه الأنظمة معلومات قيّمة حول توزيع الضغط على القدم وأنماط المشي لأفراد مختلفين. ومع ذلك، فإن تصميم وتنفيذ مثل هذه الأنظمة يواجه العديد من التحديات، مثل اختيار الحسّاسات والمعايرة ومعالجة البيانات والتفسير. في هذه الدراسة، نقترح نظام نعل حساس باستخدام مقاومات استشعار القوى  لقياس الضغط المطبّق من القدم على مناطق مختلفة من النعل. يقوم هذا النظام بتصنيف أربعة أنواع من تشوهات القدم: طبيعي، مسطح، انحراف القدم إلى الداخل، وزيادة انحراف القدم إلى الخارج. تستخدم مرحلة التصنيف قيم الضغط الفرقية على نقاط الضغط كمدخلات لنموذج التغذية الأمامية للشبكات العصبية. تم جمع البيانات من 60 فرداً تم تشخيصهم بالحالات المدروسة. حقق تنفيذ التغذية الأمامية للشبكات العصبية دقة بنسبة 96.6٪ باستخدام 50٪ من المجموعة البيانية كبيانات تدريبية و 92.8٪ باستخدام 30٪ من البيانات التدريبية فقط. ويوضح المقارنة مع الأعمال ذات الصلة الأثر الإيجابي لاستخدام القيم الفرق لنقاط الضغط كمدخلات للشبكات العصبية مقارنة بالبيانات الأولية.Sensing insole systems are a promising technology for various applications in healthcare and sports. They can provide valuable information about the foot pressure distribution and gait patterns of different individuals. However, designing and implementing such systems poses several challenges, such as sensor selection, calibration, data processing, and interpretation. This paper proposes a sensing insole system that uses force-sensitive resistors (FSRs) to measure the pressure exerted by the foot on different regions of the insole. This system classifies four types of foot deformities: normal, flat, over-pronation, and excessive supination. The classification stage uses the differential values of pressure points as input for a feedforward neural network (FNN) model. Data acquisition involved 60 subjects diagnosed with the studied cases. The implementation of FNN achieved an accuracy of 96.6% using 50% of the dataset as training data and 92.8% using only 30% training data. The comparison with related work shows good impact of using the differential values of pressure points as input for neural networks compared with raw data

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

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

ESTIMATION OF MULTI-DIRECTIONAL ANKLE IMPEDANCE AS A FUNCTION OF LOWER EXTREMITY MUSCLE ACTIVATION

The purpose of this research is to investigate the relationship between the mechanical impedance of the human ankle and the corresponding lower extremity muscle activity. Three experimental studies were performed to measure the ankle impedance about multiple degrees of freedom (DOF), while the ankle was subjected to different loading conditions and different levels of muscle activity. The first study determined the non-loaded ankle impedance in the sagittal, frontal, and transverse anatomical planes while the ankle was suspended above the ground. The subjects actively co-contracted their agonist and antagonistic muscles to various levels, measured using electromyography (EMG). An Artificial Neural Network (ANN) was implemented to characterize the relationship between the EMG and non-loaded ankle impedance in 3-DOF. The next two studies determined the ankle impedance and muscle activity during standing, while the foot and ankle were subjected to ground perturbations in the sagittal and frontal planes. These studies investigate the performance of subject-dependent models, aggregated models, and the feasibility of a generic, subject-independent model to predict ankle impedance based on the muscle activity of any person. Several regression models, including Least Square, Support Vector Machine, Gaussian Process Regression, and ANN, and EMG feature extraction techniques were explored. The resulting subject-dependent and aggregated models were able to predict ankle impedance with reasonable accuracy. Furthermore, preliminary efforts toward a subject-independent model showed promising results for the design of an EMG-impedance model that can predict ankle impedance using new subjects. This work contributes to understanding the relationship between the lower extremity muscles and the mechanical impedance of the ankle in multiple DOF. Applications of this work could be used to improve user intent recognition for the control of active ankle-foot prostheses

Abstracts of Papers, 89th Annual Meeting of the Virginia Academy of Science, May 25-27, 2011, University of Richmond, Richmond VA

Full abstracts of the 89th Annual Meeting of the Virginia Academy of Science, May 25-27, 2011, University of Richmond, Richmond V

The effectiveness of foot orthoses as a treatment for plantar ulceration in leprosy : a study of the efficacy, acceptability, appropriateness and implantation of a podiatric regimen

This was a holistic study. Four themes were investigated to demonstrate the effectiveness of orthotic intervention for plantar ulceration affecting leprosy impaired subjects in India. 1. Efficacy Efficacy was demonstrated, primarily, through analysis of data pertaining to a controlled trial. Thirty-seven subjects, presenting with leprosy impairments including anaesthesia and plantar ulceration, were fitted with orthoses and allocated to an experimental group. Thirty-four similar subjects, were not offered orthoses and were allocated to a control group. After 8 months 52% of the ulcers presented by Experimental group and 12% of the ulcers presented by the Control group had healed. The rationale supporting the prescription of orthoses was investigated using the EMED system. It was demonstrated that intervention with orthoses resulted in significantly lower sub pedal peak pressures than intervention with leprosy sandals. 2. Implementation and Sustain ability Ulcer assessment data from March 1994 to January 1995 were used to compare the effects of orthoses supplied by the investigator with orthoses supplied by an Indian technician. The service, evaluated on the strength of these findings, was considered to have been successfully implemented. The analysis of data, collected from January 1995 to December 1995, was used to explain why the service was not sustained at an acceptable level. 3. Acceptability Interview data were analysed to describe the attitudes of the subjects to the intervention (n = 46). Indications from the analysis were that neither ulcer status (healed or unresolved) nor group allocation (Experimental or Control) affected attitudes towards the intervention. A general indication was that the intervention was favourably endorsed. 4. Appropriateness Using the Delphi technique (n = 10), a consensus on indicators of "appropriate" impairment control measures was sought. Differences of opinion were not resolved, but group priorities were ranked and a polled response was recorded. The results of the study were similar to the criteria suggested by the Delphi contributors

Elasticity mapping for breast cancer diagnosis using tactile imaging and auxiliary sensor fusion

Tactile Imaging (TI) is a technology utilising capacitive pressure sensors to image elasticity distributions within soft tissues such as the breast for cancer screening. TI aims to solve critical problems in the cancer screening pathway, particularly: low sensitivity of manual palpation, patient discomfort during X-ray mammography, and the poor quality of breast cancer referral forms between primary and secondary care facilities. TI is effective in identifying ‘non-palpable’, early-stage tumours, with basic differential ability that reduced unnecessary biopsies by 21% in repeated clinical studies. TI has its limitations, particularly: the measured hardness of a lesion is relative to the background hardness, and lesion location estimates are subjective and prone to operator error. TI can achieve more than simple visualisation of lesions and can act as an accurate differentiator and material analysis tool with further metric development and acknowledgement of error sensitivities when transferring from phantom to clinical trials. This thesis explores and develops two methods, specifically inertial measurement and IR vein imaging, for determining the breast background elasticity, and registering tactile maps for lesion localisation, based on fusion of tactile and auxiliary sensors. These sensors enhance the capabilities of TI, with background tissue elasticity determined with MAE < 4% over tissues in the range 9 kPa – 90 kPa and probe trajectory across the breast measured with an error ratio < 0.3%, independent of applied load, validated on silicone phantoms. A basic TI error model is also proposed, maintaining tactile sensor stability and accuracy with 1% settling times < 1.5s over a range of realistic operating conditions. These developments are designed to be easily implemented into commercial systems, through appropriate design, to maximise impact, providing a stable platform for accurate tissue measurements. This will allow clinical TI to further reduce benign referral rates in a cost-effective manner, by elasticity differentiation and lesion classification in future works.Tactile Imaging (TI) is a technology utilising capacitive pressure sensors to image elasticity distributions within soft tissues such as the breast for cancer screening. TI aims to solve critical problems in the cancer screening pathway, particularly: low sensitivity of manual palpation, patient discomfort during X-ray mammography, and the poor quality of breast cancer referral forms between primary and secondary care facilities. TI is effective in identifying ‘non-palpable’, early-stage tumours, with basic differential ability that reduced unnecessary biopsies by 21% in repeated clinical studies. TI has its limitations, particularly: the measured hardness of a lesion is relative to the background hardness, and lesion location estimates are subjective and prone to operator error. TI can achieve more than simple visualisation of lesions and can act as an accurate differentiator and material analysis tool with further metric development and acknowledgement of error sensitivities when transferring from phantom to clinical trials. This thesis explores and develops two methods, specifically inertial measurement and IR vein imaging, for determining the breast background elasticity, and registering tactile maps for lesion localisation, based on fusion of tactile and auxiliary sensors. These sensors enhance the capabilities of TI, with background tissue elasticity determined with MAE < 4% over tissues in the range 9 kPa – 90 kPa and probe trajectory across the breast measured with an error ratio < 0.3%, independent of applied load, validated on silicone phantoms. A basic TI error model is also proposed, maintaining tactile sensor stability and accuracy with 1% settling times < 1.5s over a range of realistic operating conditions. These developments are designed to be easily implemented into commercial systems, through appropriate design, to maximise impact, providing a stable platform for accurate tissue measurements. This will allow clinical TI to further reduce benign referral rates in a cost-effective manner, by elasticity differentiation and lesion classification in future works

IMPROVED IMAGE QUALITY IN CONE-BEAM COMPUTED TOMOGRAPHY FOR IMAGE-GUIDED INTERVENTIONS

In the past few decades, cone-beam computed tomography (CBCT) emerged as a rapidly developing imaging modality that provides single rotation 3D volumetric reconstruction with sub-millimeter spatial resolution. Compared to the conventional multi-detector CT (MDCT), CBCT exhibited a number of characteristics that are well suited to applications in image-guided interventions, including improved mechanical simplicity, higher portability, and lower cost. Although the current generation of CBCT has shown strong promise for high-resolution and high-contrast imaging (e.g., visualization of bone structures and surgical instrumentation), it is often believed that CBCT yields inferior contrast resolution compared to MDCT and is not suitable for soft-tissue imaging. Aiming at expanding the utility of CBCT in image-guided interventions, this dissertation concerns the development of advanced imaging systems and algorithms to tackle the challenges of soft-tissue contrast resolution. The presented material includes work encompassing: (i) a comprehensive simulation platform to generate realistic CBCT projections (e.g., as training data for deep learning approaches); (ii) a new projection domain statistical noise model to improve the noise-resolution tradeoff in model-based iterative reconstruction (MBIR); (iii) a novel method to avoid CBCT metal artifacts by optimization of the source-detector orbit; (iv) an integrated software pipeline to correct various forms of CBCT artifacts (i.e., lag, glare, scatter, beam hardening, patient motion, and truncation); (v) a new 3D reconstruction method that only reconstructs the difference image from the image prior for use in CBCT neuro-angiography; and (vi) a novel method for 3D image reconstruction (DL-Recon) that combines deep learning (DL)-based image synthesis network with physics-based models based on Bayesian estimation of the statical uncertainty of the neural network. Specific clinical challenges were investigated in monitoring patients in the neurological critical care unit (NCCU) and advancing intraoperative soft-tissue imaging capability in image-guided spinal and intracranial neurosurgery. The results show that the methods proposed in this work substantially improved soft-tissue contrast in CBCT. The thesis demonstrates that advanced imaging approaches based on accurate system models, novel artifact reduction methods, and emerging 3D image reconstruction algorithms can effectively tackle current challenges in soft-tissue contrast resolution and expand the application of CBCT in image-guided interventions