A fabric-based soft hand exoskeleton for assistance: the ExHand Exoskeleton

INTRODUCTION: The rise of soft robotics has driven the development of devices for assistance in activities of daily living (ADL). Likewise, different types of actuation have been developed for safer human interaction. Recently, textile-based pneumatic actuation has been introduced in hand exoskeletons for features such as biocompatibility, flexibility, and durability. These devices have demonstrated their potential use in assisting ADLs, such as the degrees of freedom assisted, the force exerted, or the inclusion of sensors. However, performing ADLs requires the use of different objects, so exoskeletons must provide the ability to grasp and maintain stable contact with a variety of objects to lead to the successful development of ADLs. Although textile-based exoskeletons have demonstrated significant advancements, the ability of these devices to maintain stable contact with a variety of objects commonly used in ADLs has yet to be fully evaluated. MATERIALS AND METHODS: This paper presents the development and experimental validation in healthy users of a fabric-based soft hand exoskeleton through a grasping performance test using The Anthropomorphic Hand Assessment Protocol (AHAP), which assesses eight types of grasping with 24 objects of different shapes, sizes, textures, weights, and rigidities, and two standardized tests used in the rehabilitation processes of post- stroke patients. RESULTS AND DISCUSSION: A total of 10 healthy users (45.50 ± 14.93 years old) participated in this study. The results indicate that the device can assist in developing ADLs by evaluating the eight types of grasps of the AHAP. A score of 95.76 ± 2.90% out of 100% was obtained for the Maintaining Score, indicating that the ExHand Exoskeleton can maintain stable contact with various daily living objects. In addition, the results of the user satisfaction questionnaire indicated a positive mean score of 4.27 ± 0.34 on a Likert scale ranging from 1 to 5

Clinical utility of a pediatric hand exoskeleton: identifying users, practicability, and acceptance, and recommendations for design improvement

BACKGROUND Children and adolescents with upper limb impairments can experience limited bimanual performance reducing daily-life independence. We have developed a fully wearable pediatric hand exoskeleton (PEXO) to train or compensate for impaired hand function. In this study, we investigated its appropriateness, practicability, and acceptability. METHODS Children and adolescents aged 6-18 years with functional limitations in at least one hand due to a neurological cause were selected for this cross-sectional evaluation. We characterized participants by various clinical tests and quantified bimanual performance with the Assisting Hand Assessment (AHA). We identified children whose AHA scaled score increased by ≥ 7 points when using the hand exoskeleton and determined clinical predictors to investigate appropriateness. The time needed to don each component and the number of technical issues were recorded to evaluate practicability. For acceptability, the experiences of the patients and the therapist with PEXO were evaluated. We further noted any adverse events. RESULTS Eleven children (median age 11.4 years) agreed to participate, but data was available for nine participants. The median AHA scaled score was higher with PEXO (68; IQR: 59.5-83) than without (55; IQR: 37.5-80.5; p = 0.035). The Box and Block test, the Selective Control of the Upper Extremity Scale, and finger extensor muscle strength could differentiate well between those participants who improved in AHA scaled scores by ≥ 7 points and those who did not (sensitivity and specificity varied between 0.75 and 1.00). The median times needed to don the back module, the glove, and the hand module were 62, 150, and 160 s, respectively, but all participants needed assistance. The most critical failures were the robustness of the transmission system, the electronics, and the attachment system. Acceptance was generally high, particularly in participants who improved bimanual performance with PEXO. Five participants experienced some pressure points. No adverse events occurred. CONCLUSIONS PEXO is a safe exoskeleton that can improve bimanual hand performance in young patients with minimal hand function. PEXO receives high acceptance. We formulated recommendations to improve technical issues and the donning before such exoskeletons can be used under daily-life conditions for therapy or as an assistive device. Trial registration Not appropriate

A fabric-based soft hand exoskeleton for assistance: the ExHand Exoskeleton

Introduction: The rise of soft robotics has driven the development of devices for assistance in activities of daily living (ADL). Likewise, different types of actuation have been developed for safer human interaction. Recently, textile-based pneumatic actuation has been introduced in hand exoskeletons for features such as biocompatibility, flexibility, and durability. These devices have demonstrated their potential use in assisting ADLs, such as the degrees of freedom assisted, the force exerted, or the inclusion of sensors. However, performing ADLs requires the use of different objects, so exoskeletons must provide the ability to grasp and maintain stable contact with a variety of objects to lead to the successful development of ADLs. Although textile-based exoskeletons have demonstrated significant advancements, the ability of these devices to maintain stable contact with a variety of objects commonly used in ADLs has yet to be fully evaluated. Materials and methods: This paper presents the development and experimental validation in healthy users of a fabric-based soft hand exoskeleton through a grasping performance test using The Anthropomorphic Hand Assessment Protocol (AHAP), which assesses eight types of grasping with 24 objects of different shapes, sizes, textures, weights, and rigidities, and two standardized tests used in the rehabilitation processes of post- stroke patients. Results and discussion: A total of 10 healthy users (45.50 ± 14.93 years old) participated in this study. The results indicate that the device can assist in developing ADLs by evaluating the eight types of grasps of the AHAP. A score of 95.76 ± 2.90% out of 100% was obtained for the Maintaining Score, indicating that the ExHand Exoskeleton can maintain stable contact with various daily living objects. In addition, the results of the user satisfaction questionnaire indicated a positive mean score of 4.27 ± 0.34 on a Likert scale ranging from 1 to 5

Development of Speech Command Control Based TinyML System for Post-Stroke Dysarthria Therapy Device

Post-stroke dysarthria (PSD) is a widespread outcome of a stroke. To help in the objective evaluation of dysarthria, the development of pathological voice recognition and technology has a lot of attention. Soft robotics therapy devices have been received as an alternative rehabilitation and hand grasp assistance for improving activity daily living (ADL). Despite the significant progress in this field, most soft robotic therapy devices use a complex, bulky, lack of pathological voice recognition model, large computational power, and stationary controller. This study aims to develop a portable wirelessly multi-controller with a simulated dysarthric vowel speech in Bahasa Indonesia and non-dysarthric micro speech recognition, using tiny machine learning (TinyMl) system for hardware efficiency. The speech interface using INMP441, compute with a lightweight Deep Convolutional Neural network (DCNN) design and embedded into ESP-32. Feature model using Short Time Fourier Transform (STFT) and fed into CNN. This method has proven useful in micro-speech recognition with low computational power in both speech scenarios with a level of accuracy above 90%. Realtime inference performance on ESP-32 using hand prosthetics, with 3-level household noise intensity respectively 24db,42db, and 62db, and has respectively resulted from 95%, 85%, and 50% Accuracy. Wireless connectivity success rate with both controllers is around 0.2 - 0.5 ms