A review on the advancements in the field of upper limb prosthesis

Use of Artificial Intelligence Techniques to Assist Individuals with Physical Disabilities

Assistive technologies (AT) enable people with disabilities to perform activities of daily living more independently, have greater access to community and healthcare services, and be more productive performing educational and/or employment tasks. Integrating artificial intelligence (AI) with various agents, including electronics, robotics, and software, has revolutionized AT, resulting in groundbreaking technologies such as mind-controlled exoskeletons, bionic limbs, intelligent wheelchairs, and smart home assistants. This article provides a review of various AI techniques that have helped those with physical disabilities, including brain-computer interfaces, computer vision, natural language processing, and human-computer interaction. The current challenges and future directions for AI-powered advanced technologies are also addressed.

Recent trends and challenges of surface electromyography in prosthetic applications

Surface electromyography (sEMG) meets extensive applications in the field of prosthesis in the current period. The effectiveness of sEMG in prosthesis applications has been verified by numerous revolutionary developments and extensive research attempts. A large volume of research and literature works have explored and validated the vast use of these signals in prostheses as an assistive technology. The objective of this paper is to conduct a systematic review and offer a detailed overview of the work record in the prosthesis and myoelectric interfaces framework. This review utilized a systematic search strategy to identify published articles discussing the state-of-the-art applications of sEMG in prostheses (including upper limb prosthesis and lower limb prostheses). Relevant studies were identified using electronic databases such as PubMed, IEEE Explore, SCOPUS, ScienceDirect, Google Scholar and Web of Science. Out of 3791 studies retrieved from the databases, 188 articles were found to be potentially relevant (after screening of abstracts and application of inclusion-exclusion criteria) and included in this review. This review presents an investigative analysis of sEMG-based prosthetic applications to assist the readers in making further advancements in this field. It also discusses the fundamental advantages and disadvantages of using sEMG in prosthetic applications. It also includes some important guidelines to follow in order to improve the performance of sEMG-based prosthesis. The findings of this study support the widespread use of sEMG in prosthetics. It is concluded that sEMG-based prosthesis technology, still in its sprouting phase, requires significant explorations for further development. Supplementary investigations are necessary in the direction of making a seamless mechanism of biomechatronics for sEMG-based prosthesis by cohesive efforts of robotic researchers and biomedical engineers.

Shoulder complaints and incidence of shoulder pathologies after contralateral major amputation in the mid and long-term

INTRODUCTION

Amputations of the upper extremity are rare but present a life-altering event that is accompanied with considerable restrictions for the affected patients. Even with functional prosthesis, tasks of the amputated limb are usually transferred to the unaffected arm which could result in complaints of the unaffected shoulder in the mid and long term. We therefore aimed to investigate musculoskeletal pain and morphological degenerative changes of the shoulder following a contralateral amputation.

MATERIALS AND METHODS

We included all patients with a major amputation treated at our institution with a minimum of three years since the amputation. All patients received an MRI of both shoulders and were investigated using validated scores for the upper extremity and physical activity (SSV, ASES, DASH, GPAQ, SF-36). Results of the MRIs were investigated for morphological changes by two blinded investigators comparing the side of the amputation and the unharmed upper extremity and results were correlated to the time since amputation and their physical activity.

RESULTS

A total of 20 patients with a mean age of 56 ± 19.9 years (range, 23-82 years) could be included in the study. The mean time since the amputation was 26.3 ± 19 years (range, 3-73 years). On the unharmed upper extremity, the mean SSV was 61.9 ± 24.6, the mean ASES-Score 54.5 ± 20.3, the Constant-score of 63.7 ± 40.4 and a DASH-score of 47.6 ± 23.8. The MRI of the unharmed shoulder showed significant more full-thickness rotator cuff tears and joint effusion compared to the side of the amputation. Significant differences in the degree of a glenohumeral arthritis, AC-joint arthritis, or partial rotator cuff tears could not be found between shoulders.

CONCLUSION

Amputations of the upper extremity are associated with a high disability of the unharmed upper extremity and more full thickness rotator cuff tears compared to the side of the amputation. However, the small number of patients and rotator cuff injuries should be kept in mind when interpreting the data.

LEVEL OF EVIDENCE

IV (retrospective case series).

The Role of Fascial Tissue Layer in Electric Signal Transmission from the Forearm Musculature to the Cutaneous Layer as a Possibility for Increased Signal Strength in Myoelectric Forearm Exoprosthesis Development

Myoelectric exoprostheses serve to aid in the everyday activities of patients with forearm or hand amputations. While electrical signals are known key factors controlling exoprosthesis, little is known about how we can improve their transmission strength from the forearm muscles as to obtain better sEMG. The purpose of this study is to evaluate the role of the forearm fascial layer in transmitting myoelectrical current. We examined the sEMG signals in three individual muscles, each from six healthy forearms (Group 1) and six amputation stumps (Group 2), along with their complete biometric characteristics. Following the tests, one patient underwent a circumferential osteoneuromuscular stump revision surgery (CONM) that also involved partial removal of fascia and subcutaneous fat in the amputation stump, with re-testing after complete healing. In group 1, we obtained a stronger sEMG signal than in Group 2. In the CONM case, after surgery, the patient’s data suggest that the removal of fascia, alongside the fibrotic and subcutaneous fat tissue, generates a stronger sEMG signal. Therefore, a reduction in the fascial layer, especially if accompanied by a reduction of the subcutaneous fat layer may prove significant for improving the strength of sEMG signals used in the control of modern exoprosthetics.

Towards assessing the preferred usage features of upper limb prostheses: most important items regarding prosthesis use in people with major unilateral upper limb absence-a Dutch national survey

PURPOSE

To determine which items regarding prosthesis use were considered most important by adults with major unilateral upper limb absence (ULA) and to develop a patient-reported outcome measure to assess the preferred usage features of upper limb prostheses: PUF-ULP.

MATERIALS AND METHODS

Based on a qualitative meta-synthesis combined with input from patients and clinicians a graphical diagram of 79 items related to prosthesis use was developed. Adults with ULA (N = 358; mean age = 55.4 ± 16.5 years; 52.0% male/40.8% female/7.3% unknown) selected their top-10 of most important items from this diagram. This study is registered in the Netherlands Trial Register: NL7682.

RESULTS

Most selected items were "wearing comfort" (54.0% of cases), "grabbing, picking up, and holding" (34.3%), and "weight" (31.4%). All subpopulations (i.e. age, sex, origin of ULA, level of ULA, and prosthesis type), except multi-grip myoelectric hand prosthesis users (MHP), selected "wearing comfort" most. Nine items were included in the PUF-ULP: "wearing comfort," "functionality," "independence," "work, hobby, and household," "user-friendly," "life-like appearance," "phantom limb pain," "overuse complaints," and "reliability."

CONCLUSIONS

All prosthesis users, except MHP-users, considered wearing comfort most important, which might be of interest for future research and industry. The PUF-ULP can be used to reflect the match between users and their prostheses.IMPLICATIONS FOR REHABILITATIONAll persons with upper limb absence, except multi-grip myoelectric hand prosthesis users, considered "wearing comfort" most important regarding prosthesis use, which highlights that prosthesis wearing comfort deserves more attention in future research to increase the value placed by the user on their upper limb prosthesis.Regarding prosthesis use, men considered "ease of control" more important compared to the overall population, while women considered "independence," "household," "life-like appearance," "overuse complaints," and "anonymity" more important.Persons with a mono- or multi-grip myoelectric upper limb prosthesis rated function-related items as more important compared to the overall population, while persons with a passive/cosmetic prosthesis rated comfort-related and appearance-related items as more important.The newly developed measurement tool, also called the PUF-ULP, provides a single score that represents the match between the user and their upper limb prosthesis.

A Grip Strength Estimation Method Using a Novel Flexible Sensor under Different Wrist Angles

It is a considerable challenge to realize the accurate, continuous detection of handgrip strength due to its complexity and uncertainty. To address this issue, a novel grip strength estimation method oriented toward the multi-wrist angle based on the development of a flexible deformation sensor is proposed. The flexible deformation sensor consists of a foaming sponge, a Hall sensor, an LED, and photoresistors (PRs), which can measure the deformation of muscles with grip strength. When the external deformation squeezes the foaming sponge, its density and light intensity change, which is detected by a light-sensitive resistor. The light-sensitive resistor extended to the internal foaming sponge with illuminance complies with the extrusion of muscle deformation to enable relative muscle deformation measurement. Furthermore, to achieve the speed, accuracy, and continuous detection of grip strength with different wrist angles, a new grip strength-arm muscle model is adopted and a one-dimensional convolutional neural network based on the dynamic window is proposed to recognize wrist joints. Finally, all the experimental results demonstrate that our proposed flexible deformation sensor can accurately detect the muscle deformation of the arm, and the designed muscle model and convolutional neural network can continuously predict hand grip at different wrist angles in real-time.

The efficacy of robot-assisted training for patients with upper limb amputations who use myoelectric prostheses: a randomized controlled pilot study

The aim of this pilot study was to investigate whether a movement therapy robot can improve skills in using a myoelectric prosthesis by patients with upper limb amputations. This prospective randomized, controlled study included a total of eleven patients with upper limb amputations who use myoelectric prostheses. The patients were randomized into a robot-assisted exercise group (n = 6) and a control group (n = 5). The robot group received robot-assisted training. No training program was provided to the control group. The outcome measure was kinematic data (A-goal hand-path ratio, A-goal deviation, A-goal instability and A-move) evaluated by the Armeo®Spring movement therapy robot. Significant improvements were noted in the A-goal hand-path ratio; A-goal deviation and A-goal instability in the robot group after treatment while compared with control group. No significant changes in A-move scores. We concluded that robot-assisted training may improve myoelectric prosthesis use skills in patients with upper limb amputation.

A Way of Bionic Control Based on EI, EMG, and FMG Signals

Creating highly functional prosthetic, orthotic, and rehabilitation devices is a socially relevant scientific and engineering task. Currently, certain constraints hamper the development of such devices. The primary constraint is the lack of an intuitive and reliable control interface working between the organism and the actuator. The critical point in developing these devices and systems is determining the type and parameters of movements based on control signals recorded on an extremity. In the study, we investigate the simultaneous acquisition of electric impedance (EI), electromyography (EMG), and force myography (FMG) signals during basic wrist movements: grasping, flexion/extension, and rotation. For investigation, a laboratory instrumentation and software test setup were made for registering signals and collecting data. The analysis of the acquired signals revealed that the EI signals in conjunction with the analysis of EMG and FMG signals could potentially be highly informative in anthropomorphic control systems. The study results confirm that the comprehensive real-time analysis of EI, EMG, and FMG signals potentially allows implementing the method of anthropomorphic and proportional control with an acceptable delay.

Attitudes May Be Hard to Change: Canadian Organ Donors Consider Face and Hand Donation

Despite the success of composite tissue allograft (CTA) such as face and hand transplant at improving recipients’ quality of life, organ donors’ hesitation needs to be better understood. The aim of the study was to assess Canadian organ donors’ willingness to donate their face and hands, and the efficacy of an educational intervention.

Impact of the choice of upper limb prosthesis mechanism on kinematics and dynamic quality

Upper limb prostheses can greatly improve the condition of amputees. However, prosthetic mechanisms have different topologies and there is no consensus on the choice of an appropriate mechanism. This paper evaluates the impact of prosthetic mechanism topology on the prosthesis' performance during daily tasks. The proposed multibody model is compared to four open-loop and one closed-loop existing mechanisms according to: (1) consumed energy, (2) global and local movement reconstruction errors during inverse kinematics, (3) movement smoothness, which reflects the dynamic appearance of the prosthesis, also called 'dynamic cosmesis'. Flexion-extension (FE) and pronation-supination (PS) tasks were studied in 15 healthy subjects. All parameters identified at least one group difference (p < 0.0001) in both tasks. Most closed-loop mechanisms (50% in FE and 100 % in PS) including the proposed model were among the most energy-efficient mechanisms. Out of all models, the proposed model was the most energy efficient in FE (2.07 ± 0.69 KJ) and in PS (0.25 ±  0.16 KJ). This model also reproduced the studied movements with the lowest errors (1.39 ± 0.2 mm in FE and 1.38 ± 0.25 mm in PS), especially at the forearm level. The results show that the wrist plays a major role in motion smoothness and that two series mechanisms have exhibited a poor dynamic cosmesis because of their higher jerk cost ((1.73 ± 0.30) × 10¹⁰) in FE and (9.29 ± 17) × 10¹³ in PS tasks)). Finally, the mechanism topology affects the performance of upper limb prostheses and represents a novel aspect in the prostheses design which can be applied to exoskeleton design.

Reduce Surface Electromyography Channels for Gesture Recognition by Multitask Sparse Representation and Minimum Redundancy Maximum Relevance

Surface electromyography- (sEMG-) based gesture recognition is widely used in rehabilitation training, artificial prosthesis, and human-computer interaction. The purpose of this study is to simplify the sEMG devices by reducing channels while achieving comparably high gesture recognition accuracy. We propose a compound channel selection scheme by combining the variable selection algorithms based on multitask sparse representation (MTSR) and minimum Redundancy Maximum Relevance (mRMR). Specifically, channelwise features are first extracted to compose channel-feature paired variables, for which variable selection procedures by MTSR and mRMR are carried out, respectively. Then, we rank all the channels according to their occurrences in each variable selection procedure and figure out a certain number of informative channels by fusing these rankings of channels. Finally, the gesture classification performance using the selected channels is evaluated by the support vector machine (SVM) classifier. Experiment results validate the effectiveness of this proposed method.

Can Prosthetic Hands Mimic a Healthy Human Hand?

Historical evidence suggests that prostheses have been used since ancient Egyptian times. Prostheses were usually utilized for function and cosmetic appearances. Nowadays, with the advancement of technology, prostheses such as artificial hands can not only improve functional, but have psychological advantages as well and, therefore, can significantly enhance an individual’s standard of living. Combined with advanced science, a prosthesis is not only a simple mechanical device, but also an aesthetic, engineering and medical marvel. Prosthetic limbs are the best tools to help amputees reintegrate into society. In this article, we discuss the background and advancement of prosthetic hands with their working principles and possible future implications. We also leave with an open question to the readers whether prosthetic hands could ever mimic and replace our biological hands.

A review of technology, materials and R&D challenges of upper limb prosthesis for improved user suitability

Introduction

Hand amputation significantly challenges one's independence in carrying out daily activities. With the UK and Italy recoding circa 5200 and 3500 upper limb (UL) amputations (ULAs) yearly, respectively, and about 541,000 Americans losing ULs in 2005, incidence victims constitute a considerable proportion of our population and should be adequately supported. The use of upper limb prosthesis (ULP) offers amputees a new opportunity of living a quality life - but poses challenges on the physically and psychologically traumatised. With reports that up to 20% of adult UL amputees choose not to use a prosthesis, roughly 26% of adults and 45% of children and adolescents are dissatisfied with their devices and abandon them with reasons of poor solution to basic needs, a review of ULP for suitability has become crucial.

Objectives

These include, to review UL prosthetic technology (PT), the materials used in the manufacturing of ULP, challenges in research and development of ULP, and to advise on the suitability of different devices to the needs of amputees.

Methods

They involve an extensive review of relevant literature and application of statistics to analyse data obtained from literature.

Results

ULAs are characterised to show affected bones in seven types of amputations. The characterisation depicts key causes of incidences that lead to amputations while advising on device suitability. PT is classified in terms of cost, nature, functions/operations of each type of device while providing the design challenges. Users' opinions on PT materials are analysed and used to suggest new materials for the next generation of the devices. R&D challenges hindering future developments of PT is reviewed and results used to identify characteristics for the next generation of the technology.

Conclusions

To increase user satisfaction and reduce device abandonment, amputees need useful information on the trend in PT and engineers need information about device field performance for improvements. The use of better performing ULP will improve users' everyday lives.

A Roadmap Towards Standards for Neurally Controlled End Effectors

The control and manipulation of various types of end effectors such as powered exoskeletons, prostheses, and ‘neural’ cursors by brain-machine interface (BMI) systems has been the target of many research projects. A seamless “plug and play” interface between any BMI and end effector is desired, wherein similar user's intent cause similar end effectors to behave identically. This report is based on the outcomes of an IEEE Standards Association Industry Connections working group on End Effectors for Brain-Machine Interfacing that convened to identify and address gaps in the existing standards for BMI-based solutions with a focus on the end-effector component. A roadmap towards standardization of end effectors for BMI systems is discussed by identifying current device standards that are applicable for end effectors. While current standards address basic electrical and mechanical safety, and to some extent, performance requirements, several gaps exist pertaining to unified terminologies, data communication protocols, patient safety and risk mitigation.

A functional assembly framework based on implementable neurobionic material

Neurobionic material is an emerging field in material and translational science. For material design, much focus has already been transferred from von Neumann architecture to the neuromorphic framework. As it is impractical to reconstruct the real neural tissue solely from materials, it is necessary to develop a feasible neurobionics framework to realize advanced brain function. In this study, we proposed a mathematical neurobionic material model, and attempted to explore advanced function only by simple and feasible structures. Here an equivalent simplified framework was used to describe the dynamics expressed in an equation set, while in vivo study was performed to verify simulation results. In neural tissue, the output of neurobionic material was characterized by spike frequency, and the stability is based on the excitatory/inhibitory proportion. Spike frequency in mathematical neurobionic material model can spontaneously meet the solution of a nonlinear equation set. Assembly can also evolve into a certain distribution under different stimulations, closely related to decision making. Short-term memory can be formed by coupling neurobionic material assemblies. In vivo experiments further confirmed predictions in our mathematical neurobionic material model. The property of this neural biomimetic material model demonstrates its intrinsic neuromorphic computational ability, which should offer promises for implementable neurobionic device design.