Search Results (17)

This study presents the design, fabrication, and clinical validation of a lightweight, body-powered prosthetic index finger actuated via metacarpophalangeal (MCP) joint motion. The proposed system incorporates an underactuated, cable-driven mechanism combining rigid and compliant elements to achieve passive adaptability and embodied intelligence, supporting intuitive user interaction. Results indicate that the prosthesis successfully mimics natural finger flexion and adapts effectively to a variety of grasping tasks with minimal effort. This study was conducted in accordance with ethical standards and approved by the Institutional Review Board (IRB), Project No. 670161, titled “Biologically-Inspired Synthetic Finger: Design, Fabrication, and Application.” The findings suggest that the device offers a viable and practical solution for individuals with partial hand loss, particularly in settings where electrically powered systems are unsuitable or inaccessible. Full article

Hands are central to nearly every aspect of daily life, so losing an upper limb due to amputation can severely affect a person’s independence. Robotic prostheses offer a promising solution by mimicking many of the functions of a natural arm, leading to an increasing need for advanced prosthetic designs. However, developing an effective robotic hand prosthesis is far from straightforward. It involves several critical steps, including creating accurate models, choosing materials that balance biocompatibility with durability, integrating electronic and sensory components, and perfecting control systems before final production. A key factor in ensuring smooth, natural movements lies in the method of control. One popular approach is to use electromyography (EMG), which relies on electrical signals from the user’s remaining muscle activity to direct the prosthesis. By decoding these signals, we can predict the intended hand and arm motions and translate them into real-time actions. Recent strides in machine learning have made EMG-based control more adaptable, offering users a more intuitive experience. Alongside this, researchers are exploring tactile sensors for enhanced feedback, materials resilient in harsh conditions, and mechanical designs that better replicate the intricacies of a biological limb. This review brings together these advancements, focusing on emerging trends and future directions in robotic upper-limb prosthesis development. Full article

Surface electromyography (sEMG) signals reflect the local electrical activity of muscle fibers and the synergistic action of the overall muscle group, making them useful for gesture control of myoelectric manipulators. In recent years, deep learning methods have increasingly been applied to sEMG gesture recognition due to their powerful automatic feature extraction capabilities. sEMG signals contain rich local details and global patterns, but single-scale convolutional networks are limited in their ability to capture both comprehensively, which restricts model performance. This paper proposes a deep learning model based on multi-scale feature fusion—MS-CLSTM (MS Block-ResCBAM-Bi-LSTM). The MS Block extracts local details, global patterns, and inter-channel correlations in sEMG signals using convolutional kernels of different scales. The ResCBAM, which integrates CBAM and Simple-ResNet, enhances attention to key gesture information while alleviating overfitting issues common in small-sample datasets. Experimental results demonstrate that the MS-CLSTM model achieves recognition accuracies of 86.66% and 83.27% on the Ninapro DB2 and DB4 datasets, respectively, and the accuracy can reach 89% in real-time myoelectric manipulator gesture prediction experiments. The proposed model exhibits superior performance in sEMG gesture recognition tasks, offering an effective solution for applications in prosthetic hand control, robotic control, and other human–computer interaction fields. Full article

This study develops biomimetic strategies for slip prevention in prosthetic hand grasps. The biomimetic system is driven by a novel slip sensor, followed by slip perception and preventive control. Here, we show that biologically inspired sensorimotor pathways can be restored between the prosthetic hand and users. A Ruffini endings-like slip sensor is used to detect shear forces and identify slip events directly. The slip information and grip force are encoded into a bi-state sensory coding that evokes vibration and buzz tactile sensations in subjects with transcutaneous electrical nerve stimulation (TENS). Subjects perceive slip events under various conditions based on the vibration sensation and voluntarily adjust grip force to prevent further slipping. Additionally, short-latency compensation for grip force is also implemented using a neuromorphic reflex pathway. The reflex loop includes a sensory neuron and interneurons to adjust the activations of antagonistic muscles reciprocally. The slip prevention system is tested in five able-bodied subjects and two transradial amputees with and without reflex compensation. A psychophysical test for perception reveals that the slip can be detected effectively, with a success accuracy of 96.57%. A slip protection test indicates that reflex compensation yields faster grasp adjustments than voluntary action, with a median response time of 0.30 (0.08) s, a rise time of 0.26 (0.03) s, an execution time of 0.56 (0.07) s, and a slip distance of 0.39 (0.10) cm. Prosthetic grip force is highly correlated to that of an intact hand, with a correlation coefficient of 96.85% (2.73%). These results demonstrate that it is feasible to reconstruct slip biomimetic sensorimotor pathways that provide grasp stability for prosthetic users. Full article

Researchers have attempted to control robotic hands and prostheses through biosignals but could not match the human hand. Surface electromyography records electrical muscle activity using non-invasive electrodes and has been the primary method in most studies. While surface electromyography-based hand motion decoding shows promise, it has not yet met the requirements for reliable use. Combining different sensing modalities has been shown to improve hand gesture classification accuracy. This work introduces a multimodal bracelet that integrates a 24-channel force myography system with six commercial surface electromyography sensors, each containing a six-axis inertial measurement unit. The device’s functionality was tested by acquiring muscular activity with the proposed device from five participants performing five different gestures in a random order. A random forest model was then used to classify the performed gestures from the acquired signal. The results confirmed the device’s functionality, making it suitable to study sensor fusion for intent detection in future studies. The results showed that combining all modalities yielded the highest classification accuracies across all participants, reaching $92.3\pm 2.6\%$ on average, effectively reducing misclassifications by 37% and 22% compared to using surface electromyography and force myography individually as input signals, respectively. This demonstrates the potential benefits of sensor fusion for more robust and accurate hand gesture classification and paves the way for advanced control of robotic and prosthetic hands. Full article

Myoelectric hands are beneficial tools in the daily activities of people with upper-limb deficiencies. Because traditional myoelectric hands rely on detecting muscle activity in residual limbs, they are not suitable for individuals with short stumps or paralyzed limbs. Therefore, we developed a novel electric prosthetic hand that functions without myoelectricity, utilizing wearable wireless sensor technology for control. As a preliminary evaluation, our prototype hand with wireless button sensors was compared with a conventional myoelectric hand (Ottobock). Ten healthy therapists were enrolled in this study. The hands were fixed to their forearms, myoelectric hand muscle activity sensors were attached to the wrist extensor and flexor muscles, and wireless button sensors for the prostheses were attached to each user’s trunk. Clinical evaluations were performed using the Simple Test for Evaluating Hand Function and the Action Research Arm Test. The fatigue degree was evaluated using the modified Borg scale before and after the tests. While no statistically significant differences were observed between the two hands across the tests, the change in the Borg scale was notably smaller for our prosthetic hand (p = 0.045). Compared with the Ottobock hand, the proposed hand prosthesis has potential for widespread applications in people with upper-limb deficiencies. Full article

Designs of active prostheses attempt to compensate for various functional losses following amputation. Integration of sensory feedback with the functional control re-enables sensory interaction with the environment through the prosthetic. Besides the functional and sensory loss, amputation induces anatomical and physiological changes of the sensory neural pathways, both peripherally and centrally, which can lead to phantom limb pain (PLP). Additionally, referred sensation areas (RSAs) likely originating from peripheral nerve sprouting, regeneration, and sensory reinnervation may develop. RSAs might provide a non-invasive access point to sensory neural pathways that project to the lost limb. This paper aims to report on the sensory input features, elicited using non-invasive electrical stimulation of RSAs that over time alleviated PLP in two upper-limb amputees. The distinct features of RSAs and sensation evoked using mechanical and electrical stimuli were characterized for the two participants over a period of 7 and 9 weeks, respectively. Both participants received transradial and transhumeral amputation following traumatic injuries. In one participant, a relatively low but stable number of RSAs provided a large variety of types of evoked phantom hand (PH) sensations. These included non-painful touch, vibration, tingling, stabbing, pressure, warmth/cold as well as the perception of various positions and movements of the phantom hand upon stimulation. Discomforting and painful sensations were induced with both mechanical and electrical stimuli. The other participant had a relatively large number of RSAs which varied over time. Stimulation of the RSAs provided mostly non-painful sensations of touch in the phantom hand. Temporary PLP alleviation and a change in the perception of the phantom hand from a tight to a more open fist were reported by both participants. The specificity of RSAs, dynamics in perception of the sensory input, and the associated alleviation of PLP could be effectively exploited by designs of future active prostheses. As such, techniques for the modulation of the sensory input associated with paradigms from interaction with the environment may add another dimension of protheses towards integrating personalized therapy for PLP. Full article

Surface electromyography (sEMG) is a non-invasive measure of electrical activity generated due to muscle contraction. In recent years, sEMG signals have been increasingly used in diverse applications such as rehabilitation, pattern recognition, and control of orthotic and prosthetic systems. This study presents the development of a versatile multi-channel sEMG low-cost wearable band system to acquire 4 signals. In this case, the signals acquired with the proposed device have been used to detect hand movements. However, the WyoFlex band could be used in some sections of the arm or the leg if the section’s diameter matches the diameter of the WyoFlex band. The designed WyoFlex band was fabricated using three-dimensional (3D) printing techniques employing thermoplastic polyurethane and polylactic acid as manufacturing materials. Then, the proposed wearable electromyographic system (WES) consists of 2 WyoFlex bands, which simultaneously allow the wireless acquisition of 4 sEMG channels of each forearm. The collected sEMG can be visualized and stored for future post-processing stages using a graphical user interface designed in Node-RED. Several experimental tests were conducted to verify the performance of the WES. A dataset with sEMG collected from 15 healthy humans has been obtained as part of the presented results. In addition, a classification algorithm based on artificial neural networks has been implemented to validate the usability of the collected sEMG signals. Full article

Electromyography (EMG) is the resulting electrical signal from muscle activity, commonly used as a proxy for users’ intent in voluntary control of prosthetic devices. EMG signals are recorded with gold standard Ag/AgCl gel electrodes, though there are limitations in continuous use applications, with potential skin irritations and discomfort. Alternative dry solid metallic electrodes also face long-term usability and comfort challenges due to their inflexible and non-breathable structures. This is critical when the anatomy of the targeted body region is variable (e.g., residual limbs of individuals with amputation), and conformal contact is essential. In this study, textile electrodes were developed, and their performance in recording EMG signals was compared to gel electrodes. Additionally, to assess the reusability and robustness of the textile electrodes, the effect of 30 consumer washes was investigated. Comparisons were made between the signal-to-noise ratio (SNR), with no statistically significant difference, and with the power spectral density (PSD), showing a high correlation. Subsequently, a fully textile sleeve was fabricated covering the forearm, with 14 textile electrodes. For three individuals, an artificial neural network model was trained, capturing the EMG of 7 distinct finger movements. The personalized models were then used to successfully control a myoelectric prosthetic hand. Full article

Porous piezoresistive sensors offer promising flexible sensing functionality, such as human joint motion detection and gesture identification. Herein, a facile fabrication method is developed using a microwave-based rapid porogen removal technique for the manufacturing of porous nanocomposite sponges consisting of polydimethylsiloxane (PDMS) and well-dispersed carbon nanotubes (CNTs). The porogen amounts and CNT loadings are varied to tailor the porosity and electrical properties of the porous sensors. The sponges are characterized by a scanning electron microscope (SEM) to compare their microstructures, validate the high-quality CNT dispersion, and confirm the successful nanofiller embedding within the elastomeric matrix. Sponges with a 3 wt% CNT loading demonstrate the highest piezoresistive sensitivity. Experimental characterization shows that the sponges with low porosity have long durability and minimal strain rate dependence. Additionally, the developed sponges with 3 wt% CNTs are employed for the human motion detection using piezoresistive method. One experiment includes fingertip compression measurements on a prosthetic hand. Moreover, the sensors are attached to the chest, elbow, and knee of a user to detect breathing, running, walking, joint bending, and throwing motions. Full article

The loss of one or multiple fingers can lead to psychological problems as well as functional impairment. Various options exist for replacement and restoration after hand or finger loss. Prosthetic hand or finger prostheses improve esthetic outcomes and the quality of life for patients. Myoelectrically controlled hand prostheses have been used to attempt to produce different movements. The available articles (original research articles and review articles) on myoelectrically controlled finger/hand prostheses from January 1922 to February 2021 in English were reviewed using MEDLINE/PubMed, Web of Science, and ScienceDirect resources. The articles were searched using the keywords “finger/hand loss”, “finger prosthesis”, “myoelectric control”, and “prostheses” and relevant articles were selected. Myoelectric or electromyography (EMG) signals are read by myoelectrodes and the signals are amplified, from which the muscle’s naturally generated electricity can be measured. The control of the myoelectric (prosthetic) hands or fingers is important for artificial hand or finger movement; however, the precise control of prosthetic hands or fingers remains a problem. Rehabilitation after multiple finger loss is challenging. Implants in finger prostheses after multiple finger loss offer better finger prosthesis retention. This article presents an overview of myoelectric control regarding finger prosthesis for patients with finger implants following multiple finger loss. Full article

Most commercial prosthetic hands lack closed-loop feedback, thus, a lot of research has been focusing on implementing sensory feedback systems to provide the user with sensory information during activities of daily living. This study evaluates the possibilities of using a microphone and electrotactile feedback to identify different textures. A condenser microphone was used as a sensor to detect the friction sound generated from the contact between different textures and the microphone. The generated signal was processed to provide a characteristic electrical stimulation presented to the participants. The main goal of the processing was to derive a continuous and intuitive transfer function between the microphone signal and stimulation frequency. Twelve able-bodied volunteers participated in the study, in which they were asked to identify the stroked texture (among four used in this study: Felt, sponge, silicone rubber, and string mesh) using only electrotactile feedback. The experiments were done in three phases: (1) Training, (2) with-feedback, (3) without-feedback. Each texture was stroked 20 times each during all three phases. The results show that the participants were able to differentiate between different textures, with a median accuracy of 85%, by using only electrotactile feedback with the stimulation frequency being the only variable parameter. Full article

The loss of a hand can significantly affect one’s work and social life. For many patients, an artificial limb can improve their mobility and ability to manage everyday activities, as well as provide the means to remain independent. This paper provides an extensive review of available biosensing methods to implement the control system for transradial prostheses based on the measured activity in remnant muscles. Covered techniques include electromyography, magnetomyography, electrical impedance tomography, capacitance sensing, near-infrared spectroscopy, sonomyography, optical myography, force myography, phonomyography, myokinetic control, and modern approaches to cineplasty. The paper also covers combinations of these approaches, which, in many cases, achieve better accuracy while mitigating the weaknesses of individual methods. The work is focused on the practical applicability of the approaches, and analyses present challenges associated with each technique along with their relationship with proprioceptive feedback, which is an important factor for intuitive control over the prosthetic device, especially for high dexterity prosthetic hands. Full article

Finger amputations are the most common upper limb amputation, and they occur approximately 100 times more often than hand amputations. We developed a prosthetic hand for amputees with a thumb and metacarpal. In this case of amputation, the installation of actuators and electrical components is difficult because space is considerably limited owing to the residual metacarpal. This design issue is solved by installing actuators vertically between finger modules and the mounting part where the electrical parts are embedded. With this design, the arrangement between the palm of the patient and the fingers of the prosthetic hand can be adjusted as well. Weight is also an especially important design issue in the development of a practical prosthetic hand because the patient perceives that weight. Most prosthetic hands are attached to the residual limb of the amputee by compressing the contact surface between the product and the amputated body part of the patient. Heavy weight causes users to feel discomfort and fatigue over extended periods of usage. In this study, all frames used in the proposed prosthetic hand were fabricated from nylon using multi-jet-fusion three-dimensional printing. As a result, the weight of the developed prosthetic hand was only 152.32 g but still had the desired strength and stiffness. Each prosthetic finger has four-degree-of-freedom. The distal interphalangeal, proximal interphalangeal, and metacarpophalangeal joints are coupled and driven by power from an actuator, which is transferred to each joint through the tendons. Adduction, abduction, and self-adaptive grasping motions were passively realized using linear and torsional springs. The prototype was fabricated based on these design concepts and functions, and its functionality was verified in experiments using diverse objects. Full article

Tactile sensors are widely employed to enable the sense of touch for applications such as robotics and prosthetics. In addition to the selection of an appropriate sensing material, the performance of the tactile sensing system is conditioned by its interface electronic system. On the other hand, due to the need to embed the tactile sensing system into a prosthetic device, strict requirements such as small size and low power consumption are imposed on the system design. This paper presents the experimental assessment and characterization of an interface electronic system for piezoelectric tactile sensors for prosthetic applications. The interface electronic is proposed as part of a wearable system intended to be integrated into an upper limb prosthetic device. The system is based on a low power arm-microcontroller and a DDC232 device. Electrical and electromechanical setups have been implemented to assess the response of the interface electronic with PVDF-based piezoelectric sensors. The results of electrical and electromechanical tests validate the correct functionality of the proposed system. Full article