Sensory systems in micro-processor controlled prosthetic leg: a review

Micro-processor controlled prosthetic legs (MPCPL) offer better functionality than conventional prosthetic legs as they use actuators to replace missing joint function. This potentially reduces the user's metabolic energy consumption and normal walking gait can be mimicked as closely as possible. However, MPCPL require a good control system to perform efficiently, and one of the essential components is the system of sensors. The sensory system must satisfy two important criteria; the practicality in donning and doffing the prosthesis, i.e. the process of putting on and taking off the prosthesis by the amputee user, and the quality in the information provided. In this paper, a comprehensive review was conducted on studies related to the state of the art of sensory system adopted in MPCPL. The publications were searched using four electronics databases within the last 13 years. A total of 31 papers were reviewed. The articles were classified into three main categories: prosthetic-device oriented, user's-biological-input oriented and neuro-mechanical fusion sensory system. Types of sensors used and their application to the prosthetic system were analyzed. This review indicates that the sensors technology reported in the literature still does not fulfil the criteria of an efficient sensory system. Hence, a sensory system that eases the don and doff process of the prosthesis, yet informative in terms of providing enough useful data to effectively control the prosthesis, is needed for a successful MPCPL

In-socket sensory system with an adaptive neuro-based fuzzy inference system for active transfemoral prosthetic legs

An in-socket sensory system enables the monitoring of transfemoral amputee movement for a microprocessor-controlled prosthetic leg. User movement recognition from an in-socket sensor allows a powered prosthetic leg to actively mimic healthy ambulation, thereby reducing an amputee's metabolic energy consumption. This study established an adaptive neurofuzzy inference system (ANFIS)-based control input framework from an in-socket sensor signal for gait phase classification to derive user intention as read by in-socket sensor arrays. Particular gait phase recognition was mapped with the cadence and torque control output of a knee joint actuator. The control input framework was validated with 30 experimental gait samples of the in-socket sensory signal of a transfemoral amputee walking at fluctuating speeds of 0 to 2 km · h- 1. The physical simulation of the controller presented a realistic simulation of the actuated knee joint in terms of a knee mechanism with 95% to 99% accuracy of knee cadence and 80% to 90% accuracy of torque compared with those of normal gait. The ANFIS system successfully detected the seven gait phases based on the amputee's in-socket sensor signals and assigned accurate knee joint torque and cadence values as output. © 2018 SPIE and IS&T

PROBLEM BASED LEARNING IN MANAGEMENT AND CLINICAL ENGINEERING COURSE

This paper addressed student perceptions and opinion of the problem based learning method, as well as the empirically collected data on students' learning outcomes on a Biomedical Engineering course, i.e. Management and Clinical Engineering. Pure lecture delivery with absence of practical intervention was deemed insufficient to provide appropriate means to achieve the course objectives. Therefore, a Mock Company assignment was introduced in this course as a problem based learning application aimed to aid the achievement of the program outcome while improving the attainment of the course objectives. The students were divided into groups to form individual mock company. Each mock company formed their organization post for each member, and came up with a business plan for a new project to be presented for fund approval by the panels, made up of the course instructors and invited lecturers from the clinical engineering industry and hospital practitioners. The company discussion progress and performance were monitored by the instructors through the formal university e- learning platform throughout the semester with occasional response and suggestions. The panels identified the expected lack of business and management knowledge but this was counteracted by the reasonably successful business plan produced independently by all companies’ At the end of the semester, through questionnaires, 69.6% of the 56 students agreed that this mock company assignment was useful in achieving the course objectives and should be conducted in the following years. Students who performed weakly in this assignment also demonstrated lower performance in all evaluations including by traditional means (p = 0.01), although there were no direct associations amongst the problem-based and the traditional evaluations (r <0.66). The students’ responses also reflected their readiness to perform more independent learning approaches, despite them expressing the lack of clear scope and guideline, which is the nature of a problem-based learning experience

Electrical stimulator with mechanomyography-based real-time monitoring, muscle fatigue detection, and safety shut-off: a pilot study

Functional electrical stimulation (FES) has been used to produce force-related activities on the paralyzed muscle among spinal cord injury (SCI) individuals. Early muscle fatigue is an issue in all FES applications. If not properly monitored, overstimulation can occur, which can lead to muscle damage. A real-Time mechanomyography (MMG)-based FES system was implemented on the quadriceps muscles of three individuals with SCI to generate an isometric force on both legs. Three threshold drop levels of MMG-root mean square (MMG-RMS) feature (thr50, thr60, and thr70; representing 50%, 60%, and 70% drop from initial MMG-RMS values, respectively) were used to terminate the stimulation session. The mean stimulation time increased when the MMG-RMS drop threshold increased (thr50: 22.7 s, thr60: 25.7 s, and thr70: 27.3 s), indicating longer sessions when lower performance drop was allowed. Moreover, at thr70, the torque dropped below 50% from the initial value in 14 trials, more than at thr50 and thr60. This is a clear indication of muscle fatigue detection using the MMG-RMS value. The stimulation time at thr70 was significantly longer (p = 0.013) than that at thr50. The results demonstrated that a real-Time MMG-based FES monitoring system has the potential to prevent the onset of critical muscle fatigue in individuals with SCI in prolonged FES sessions

Mechanomyographic Parameter Extraction Methods: An Appraisal for Clinical Applications

The research conducted in the last three decades has collectively demonstrated that the skeletal muscle performance can be alternatively assessed by mechanomyographic signal (MMG) parameters. Indices of muscle performance, not limited to force, power, work, endurance and the related physiological processes underlying muscle activities during contraction have been evaluated in the light of the signal features. As a non-stationary signal that reflects several distinctive patterns of muscle actions, the illustrations obtained from the literature support the reliability of MMG in the analysis of muscles under voluntary and stimulus evoked contractions. An appraisal of the standard practice including the measurement theories of the methods used to extract parameters of the signal is vital to the application of the signal during experimental and clinical practices, especially in areas where electromyograms are contraindicated or have limited application. As we highlight the underpinning technical guidelines and domains where each method is well-suited, the limitations of the methods are also presented to position the state of the art in MMG parameters extraction, thus providing the theoretical framework for improvement on the current practices to widen the opportunity for new insights and discoveries. Since the signal modality has not been widely deployed due partly to the limited information extractable from the signals when compared with other classical techniques used to assess muscle performance, this survey is particularly relevant to the projected future of MMG applications in the realm of musculoskeletal assessments and in the real time detection of muscle activity

Technology Efficacy in Active Prosthetic Knees for Transfemoral Amputees: A Quantitative Evaluation

Several studies have presented technological ensembles of active knee systems for transfemoral prosthesis. Other studies have examined the amputees’ gait performance while wearing a specific active prosthesis. This paper combined both insights, that is, a technical examination of the components used, with an evaluation of how these improved the gait of respective users. This study aims to offer a quantitative understanding of the potential enhancement derived from strategic integration of core elements in developing an effective device. The study systematically discussed the current technology in active transfemoral prosthesis with respect to its functional walking performance amongst above-knee amputee users, to evaluate the system’s efficacy in producing close-to-normal user performance. The performances of its actuator, sensory system, and control technique that are incorporated in each reported system were evaluated separately and numerical comparisons were conducted based on the percentage of amputees’ gait deviation from normal gait profile points. The results identified particular components that contributed closest to normal gait parameters. However, the conclusion is limitedly extendable due to the small number of studies. Thus, more clinical validation of the active prosthetic knee technology is needed to better understand the extent of contribution of each component to the most functional development

Technology efficacy in active prosthetic knees for transfemoral amputees: A quantitative evaluation

Several studies have presented technological ensembles of active knee systems for transfemoral prosthesis. Other studies have examined the amputees' gait performance while wearing a specific active prosthesis. This paper combined both insights, that is, a technical examination of the components used, with an evaluation of how these improved the gait of respective users. This study aims to offer a quantitative understanding of the potential enhancement derived from strategic integration of core elements in developing an effective device. The study systematically discussed the current technology in active transfemoral prosthesis with respect to its functional walking performance amongst above-knee amputee users, to evaluate the system's efficacy in producing close-to-normal user performance. The performances of its actuator, sensory system, and control technique that are incorporated in each reported system were evaluated separately and numerical comparisons were conducted based on the percentage of amputees' gait deviation from normal gait profile points. The results identified particular components that contributed closest to normal gait parameters. However, the conclusion is limitedly extendable due to the small number of studies. Thus, more clinical validation of the active prosthetic knee technology is needed to better understand the extent of contribution of each component to the most functional development

User perception on the use of a custom-built augmentative and alternative communication (AAC) device for elderly with Aphasia in Malaysia

Augmentative and alternative communication (AAC) device is one type of AAC which can be used to communicate besides oral speech. It has high potential to assist people with speech disabilities including elderly with aphasia (EWA) to communicate with others. This study was conducted using a newly built AAC device, TalkMate™, as a reference for AAC devices. This study aims to explore the views and perception of users regarding the use of AAC device for elderly with aphasia living in Malaysia. The EWA participants recruited for this study varied in age, severity level and experience with AAC. A qualitative design with five focus groups was conducted. The focus group discussion included caretakers, healthcare professionals and AAC device developers to gain information about multiple perspectives on AAC device use. Thematic analysis yielded four key themes: needs of using AAC, decision on using AAC, resources, and potential improvement of AAC for EWAs. This study highlighted the importance of understanding the needs of EWAs, decision, improvement on the quality of life of the EWAs, and the future of using AAC device. The main barriers of using AAC were identified to be due to funding and access to devices

Muscle size and strength benefits of functional electrical stimulation-evoked cycling dosage in spinal cord injury: a narrative review

Loss of sensory motor function is one of the main causes of physical and activity limitations among individual with spinal cord injury (SCI). SCI may lead to muscle paralysis, weakness and disused muscle atrophy. Evidences have shown electrical stimulation and strengthening exercise might improve lower limb muscle strength and size among individual with SCI. Functional electrical stimulation (FES) evoked cycling is one of the methods that can elicit leg muscle contractions in order to produce a cycling motion and promote the integrity of the involved muscles. Therefore, this review is to synthesize the scientific literature regarding the effects of multiple dosages of FES-evoked lower limb cycling on muscle properties. A systematic literature search from 1946 to 2016 was performed. From over 1,139 articles retrieved from the database, about 31 potentially relevant articles were retained for possible inclusion. However, only 10 articles out of 31 articles fulfilled the inclusion criteria. Although the available evidence is compelling, there is insufficient quantity and quality evidence to draw conclusions regarding the specific parameter of FES-CE that may optimally increase muscle strength, mass, and circumference. However, it can be safely concluded that an effective training session would spend for 45-60 min, 3 times a week for at least 4 weeks to see changes in muscle size and strength

Classification of standing and sitting phases based on in-socket piezoelectric sensors in a transfemoral amputee

A transfemoral prosthesis is required to assist amputees to perform the activity of daily living (ADL). The passive prosthesis has some drawbacks such as utilization of high metabolic energy. In contrast, the active prosthesis consumes less metabolic energy and offers better performance. However, the recent active prosthesis uses surface electromyography as its sensory system which has weak signals with microvolt-level intensity and requires a lot of computation to extract features. This paper focuses on recognizing different phases of sitting and standing of a transfemoral amputee using in-socket piezoelectric-based sensors. 15 piezoelectric film sensors were embedded in the inner socket wall adjacent to the most active regions of the agonist and antagonist knee extensor and flexor muscles, i. e. region with the highest level of muscle contractions of the quadriceps and hamstring. A male transfemoral amputee wore the instrumented socket and was instructed to perform several sitting and standing phases using an armless chair. Data was collected from the 15 embedded sensors and went through signal conditioning circuits. The overlapping analysis window technique was used to segment the data using different window lengths. Fifteen time-domain and frequency-domain features were extracted and new feature sets were obtained based on the feature performance. Eight of the common pattern recognition multiclass classifiers were evaluated and compared. Regression analysis was used to investigate the impact of the number of features and the window lengths on the classifiers' accuracies, and Analysis of Variance (ANOVA) was used to test significant differences in the classifiers' performances. The classification accuracy was calculated using k-fold cross-validation method, and 20% of the data set was held out for testing the optimal classifier. The results showed that the feature set (FS-5) consisting of the root mean square (RMS) and the number of peaks (NP) achieved the highest classification accuracy in five classifiers. Support vector machine (SVM) with cubic kernel proved to be the optimal classifier, and it achieved a classification accuracy of 98.33 % using the test data set. Obtaining high classification accuracy using only two time-domain features would significantly reduce the processing time of controlling a prosthesis and eliminate substantial delay. The proposed in-socket sensors used to detect sit-to-stand and stand-to-sit movements could be further integrated with an active knee joint actuation system to produce powered assistance during energy-demanding activities such as sit-to-stand and stair climbing. In future, the system could also be used to accurately predict the intended movement based on their residual limb's muscle and mechanical behaviour as detected by the in-socket sensory system