Using Artificial Intelligence To Improve The Control Of Prosthetic Legs

For as long as people have been able to survive limb threatening injuries prostheses have been created. Modern lower limb prostheses are primarily controlled by adjusting the amount of damping in the knee to bend in a suitable manner for walking and running. Often the choice of walking state or running state has to be controlled manually by pressing a button. While this simple tuning strategy can work for many users it can be limiting and there is the tendency that controlling the leg is not intuitive and the wearer has to learn how to use leg. This thesis examines how this control can be improved using Artificial Intelligence (AI) to allow the system to be tuned for each individual. A wearable gait lab was developed consisting of a number of sensors attached to the limbs of eight volunteers. The signals from the sensors were analysed and features were extracted from them which were then passed through 2 separate Artificial Neural Networks (ANN). One network attempted to classify whether the wearer was standing still, walking or running. The other network attempted to estimate the wearer’s movement speed. A Genetic Algorithm (GA) was used to tune the ANNs parameters for each individual. The results showed that each individual needed different parameters to tune the features presented to the ANN. It was also found that different features were needed for each of the two problems presented to the ANN. Two new features are presented which identify the movement states of standing, walking and running and the movement speed of the volunteer. The results suggest that the control of the prosthetic limb can be improved

Multiple sensor outputs and computational intelligence towards estimating state and speed for control of lower limb prostheses

For as long as people have been able to survive limb threatening injuries prostheses have been created. Modern lower limb prostheses are primarily controlled by adjusting the amount of damping in the knee to bend in a suitable manner for walking and running. Often the choice of walking state or running state has to be controlled manually by pressing a button. This paper examines how this control could be improved using sensors attached tofa the limbs of two volunteers. The signals from the sensors had features extracted which were passed through a computational intelligence system. The system was used to determine whether the volunteer was walking or running and their movement speed. Two new features are presented which identify the movement states of standing, walking and running and the movement speed of the volunteer. The results suggest that the control of the prosthetic limb could be improved

Embedding sustainability in university work experience placements: a De Montfort University model

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI linkPurpose – The paper looks at the feasibility of university placements supporting small and medium-scale enterprises (SMEs) to operate in a sustainable manner. Due to size and resource constraints, many SMEs may regard sustainability more as a burden than a value-adding commercial strategy. Design/methodology/approach – A two-year study was conducted on the sustainability-themed placements of 101 students of De Montfort University, United Kingdom, in SMEs. The placements were designed with the purpose of acting as a traditional work experience scheme while also equipping students with learning, skills and orientation with which to act as sustainability champions within companies. The study combined the use of students’ reflections (via tools such as monthly logbooks) with interviews and questionnaire surveys of both employers and students, in order to evaluate the outcomes of the placements. Findings – Students engaged with the sustainability aspect of their placements mainly by obtaining information on the sustainability performance of SMEs, with significant engagement also occurring in the areas of sustainability advocacy (e.g. proposing socio-environmental plans to companies) and initiatives/action. Practical implications – Placements can potentially serve as a means of knowledge generation for universities while providing SMEs with cost-effective staff and innovation sustainability resources. Originality/value – A circular approach to university placement programmes is proposed whereby the knowledge gained from previous placements about SMEs’ sustainability performance is used to prepare later cohorts of placement students with a pragmatic understanding of challenges and opportunities related to the implementation of sustainability by SMEs

Walking State Detection from Electromyographic Signals towards the Control of Prosthetic Limbs

This paper presents experiments in the use of an Electromyographic sensor to determine whether a person is standing, walking or running. The output of the sensor was captured and processed in a variety of different ways to extract those features that were seen to be changing as the movement state of the person changed. Experiments were carried out by adjusting the parameters used for the collection of the features. These extracted features where then passed to a set of Artificial Neural Networks trained to recognise each state. This methodology exhibits an accuracy needed to control a prosthetic leg

State detection from electromyographic signals towards the control of prosthetic limbs

Abstract — This paper presents experiments in the use of an Electromyographic sensor to determine whether a person is standing, walking or running. The output of the sensor was captured and processed in a variety of different ways to extract those features that were seen to be changing as the movement state of the person changed. Experiments were carried out by adjusting the parameters used for the collection of the features. These extracted features where then passed to a set of Artificial Neural Networks trained to recognise each state. This methodology exhibits an accuracy needed to control a prosthetic leg

Peer mentoring in the Placement experience search: Enhancing learning journeys across discipline boundaries

Within the Faculty of Computing, Engineering and Media at De Montfort University students seeking a year-long Placement participate in peer mentoring, enhancing the learning journey of individuals acting in the role of mentee and mentor, and operating across discipline boundaries. Supporting and empowering Placement searchers, mentoring presents an opportunity to learn from peers who have previously experienced the process, successfully securing an innovative Placement year. The scheme delivers benefits to the mentee and mentor (Hayman et al., 2022). Mentees are supported with practical tips and advice, guidance and encouragement, whilst mentors benefit through developing leadership, mentoring and communication skills, enhancing reflection to further articulate their Placement experience (Proctor, 2012). Echoing engagement with Placements across the Faculty's three schools, in 2022 the majority of mentors come from the School of Computer Science and Informatics (CSI) (55%), followed by Engineering and Sustainable Development (ESD) (36%), and then Leicester Media School (LMS) (9%). The 2022 mentees are also predominantly from CSI (76%), followed by LMS (18%), then ESD (6%). The mentor and mentee relationship crosses discipline boundaries, providing additional benefits to the learning experience by learning from the experiences and questions of those in different subject areas. Mentoring beyond discipline boundaries invites creative problem solving, active listening, and coaching. Placement returner mentors are self-selecting following a call for volunteers. Mentors support mentees to explore Placement options, develop contacts with employers, and identify suitable resources and industry links. Mentors give advice, respond to questions, share thoughts and reflections, help the mentee to develop their own aims and goals, and provide motivation, support and role-modelling. For mentees, developing an effective working relationship with a mentor enhances networking, communication and cooperation skills that will be valuable in the Placement experience and beyond. Mentees set goals around their Placement and career aspirations, regularly reviewing progress in search of a Placement. The mentoring relationship is set within a code of conduct framework based on confidentiality, valuing each member of the partnership, mutual trust and respect. Reflecting on the experience, mentees are positive about the useful advice, support and encouragement received. Mentees appreciate that mentors respond to queries and questions in a timely manner, and many pairs meet weekly to maintain regular engagement. Feedback recognises the positive impact on embracing the search for, and securing, a Placement. This presentation will introduce this approach, inspiring colleagues to extend peer mentoring applications across discipline boundaries for the benefit of all participants

Peer mentoring in the Placement experience search: Enhancing learning journeys across discipline boundaries

Within the Faculty of Computing, Engineering and Media at De Montfort University students seeking a year-long Placement participate in peer mentoring, enhancing the learning journey of individuals acting in the role of mentee and mentor, and operating across discipline boundaries. Supporting and empowering Placement searchers, mentoring presents an opportunity to learn from peers who have previously experienced the process, successfully securing an innovative Placement year. The scheme delivers benefits to the mentee and mentor (Hayman et al., 2022). Mentees are supported with practical tips and advice, guidance and encouragement, whilst mentors benefit through developing leadership, mentoring and communication skills, enhancing reflection to further articulate their Placement experience (Proctor, 2012). Echoing engagement with Placements across the Faculty's three schools, in 2022 the majority of mentors come from the School of Computer Science and Informatics (CSI) (55%), followed by Engineering and Sustainable Development (ESD) (36%), and then Leicester Media School (LMS) (9%). The 2022 mentees are also predominantly from CSI (76%), followed by LMS (18%), then ESD (6%). The mentor and mentee relationship crosses discipline boundaries, providing additional benefits to the learning experience by learning from the experiences and questions of those in different subject areas. Mentoring beyond discipline boundaries invites creative problem solving, active listening, and coaching. Placement returner mentors are self-selecting following a call for volunteers. Mentors support mentees to explore Placement options, develop contacts with employers, and identify suitable resources and industry links. Mentors give advice, respond to questions, share thoughts and reflections, help the mentee to develop their own aims and goals, and provide motivation, support and role-modelling. For mentees, developing an effective working relationship with a mentor enhances networking, communication and cooperation skills that will be valuable in the Placement experience and beyond. Mentees set goals around their Placement and career aspirations, regularly reviewing progress in search of a Placement. The mentoring relationship is set within a code of conduct framework based on confidentiality, valuing each member of the partnership, mutual trust and respect. Reflecting on the experience, mentees are positive about the useful advice, support and encouragement received. Mentees appreciate that mentors respond to queries and questions in a timely manner, and many pairs meet weekly to maintain regular engagement. Feedback recognises the positive impact on embracing the search for, and securing, a Placement. This presentation will introduce this approach, inspiring colleagues to extend peer mentoring applications across discipline boundaries for the benefit of all participants