Touch sensing has a central role in robotic grasping and emerging human–machine interfaces for robot‐assisted prosthetics. Although advancements in soft conductive polymers have promoted the creation of diverse pressure sensors, these sensors are difficult to be employed as touch skins for robotics and prostheses due to their limited sensitivity, narrow pressure range, and complex structure and fabrication process. Here, a highly sensitive and robust soft touch skin is presented with ultracapacitive sensing that combines ionic hydrogels with commercially available conductive fabrics. Prototypical designs of the capacitive sensors through facile manufacturing methods are introduced and a high sensitivity up to 1.5 kPa−1 (≈44 times higher than conventional parallel‐plate capacitive counterparts), a broad pressure detection range of over four orders of magnitudes (≈35 Pa to 330 kPa), ultrahigh baseline of capacitance, fast response time (≈18 ms), and good repeatability are demonstrated. Ionogel skins composed of an array of cutaneous mechanoreceptors capable of monitoring various physiological signals and shape detection are further developed. The touch skin can be integrated within a soft bionic hand and provide an industrial robot and an amputee with robust tactile feedback when handling delicate objects, illustrating its potential applications in next‐generation human‐in‐the‐loop robotic systems with tactile sensing.

Mainly composed of electrical motors and sophisticated mechanical components, existing neuroprosthetic hands 1,2 are typically heavy (>400 g) and expensive (>USD 10,000), and they lack the compliance and tactile feedback of human hands. These limitations hamper neuroprosthetic hands' innovation and broad utility for amputees 3-5 . Here we report the design, fabrication and applications of a lightweight (292 g) and potentially low-cost (component cost below USD 500) soft neuroprosthetic hand with simultaneous myoelectric control and tactile feedback. The soft neuroprosthetic hand consists of five soft fingers and a palm to give six active degrees of freedom under pneumatic actuation, four electromyography sensors that measure the surface electromyogram signals to control the hand to deliver four common grasp types, and five hydrogel-elastomer capacitive sensors on the fingertips that measure the touch pressure and elicit electrical stimulation on the skin of the residual limb. The soft finger is made of a fiber-reinforced elastomeric structure embedded with rigid segments to mimic the soft-joint/rigid-bone anatomy of the human finger. We use a set of standardized tests 6 to compare the speed and dexterity of the soft neuroprosthetic hand and a conventional rigid neuroprosthetic hand 7 on two transradial amputees. The soft neuroprosthetic hand gives overall superior performances to the rigid hand. We further demonstrate that one transradial amputee wearing the soft neuroprosthetic hand can regain the versatile hand functions with primitive touch sensation and real-time closed-loop control in daily activities such as handling tools, eating, shaking hands, petting animals, and recognizing touch pressure. This work not only represents a new paradigm for designing soft 2 neuroprosthetic devices but also opens an avenue to widespread applications of lightweight, low-cost, and compliant hand replacements for amputees.

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Cutaneous electrical stimulation can provide tactile feedback for upper-limb amputees through somatotopic feedback (SF) or non-somatotopic feedback (NF). The SF delivers electrotactile stimulus to projection finger maps (PFMs) on the stumps of amputees, which outperforms NF that transfers stimulus to other human intact skin areas in general. However, the SF areas on stumps are very limited and often occupied by electromyography (EMG) sensors in application of myoelectric prosthesis. This work aims at improving NF performance on human upper arms through user training with electrotactile stimulation. The experiments were conducted over seven consecutive days on nine able-bodied subjects and two forearm amputees. The performance measures of NF/SF included the correct identification rates (CIR), the response time and the NASA-TLX questionnaire. The between-day CIR s on NF sites increased logarithmically with a mean course of 3-day rapid-improving phase and plateaued in the relative-steady phase. The response time and NASA-TLX scores could also rapidly reduce to the comparable levels of the SF areas during the same mean period of 3-day rapid-improving phase, respectively. These results indicated that the performance of NF could be highly improved to the equivalent level as that of SF through 3-day electrotactile training, which we named as "3-day effect". It provides important insights that intact skin areas without phantom sensations can effectively replace SF sites to transfer tactile feedback after continuous user training, which validates effectiveness of non-invasive interfaces of tactile feedback for upper-limb amputees in practice.

Closed-loop control is important for amputees to manipulate myoelectric prostheses intuitively and dexterously. Tactile feedback can help amputees improve myoelectric control performance for grasping objects. To investigate the effects of different tactile feedback, we performed experiments on six amputees and six able-bodied subjects via electrotactile stimulation. Using a virtual environment, six kinds of objects with different weights and stiffnesses were used for grasping tasks. Five feedback conditions (no feedback, pressure feedback, slip feedback, pressure + slip feedback, and vision feedback) were considered. Nine evaluation indexes and three control objectives (rapidity, economy, and stability) were proposed. Under the five feedback conditions, our study investigated four issues: 1) three types of grasping-related failures; 2) four types of grasping-related time measures; 3) average grasping force; 4) standard deviation of the grasping force. Results indicate that: 1) slip feedback is better than pressure feedback; 2) pressure + slip feedback can improve grasping rapidity; 3) slip feedback significantly contributes to grasping economy and stability; and 4) pressure + slip feedback can perform as well as vision feedback.

BackgroundTranscutaneous electrical stimulation can provide amputees with tactile feedback for better manipulating an advanced prosthesis. In general, there are two ways to transfer the stimulus to the skin: somatotopical feedback (SF) that stimulates the phantom digit somatotopy on the stump and non-somatotopical feedback (NF) that stimulates other positions on the human body.MethodsTo investigate the difference between SF and NF, electrotactile experiments were conducted on seven amputees. Electrical stimulation was applied via a complete phantom map to the residual limb (SF) and to the upper arm (NF) separately. The behavior results of discrimination accuracy and response time were used to examine: 1) performance differences between SF and NF for discriminating position, type and strength of tactile feedback; 2) performance differences between SF and NF for one channel (1C), three channels (3C), and five channels (5C). NASA-TLX standardized testing was used to determine differences in mental workload between SF and NF.ResultsThe grand-averaged discrimination accuracy for SF was 6% higher than NF, and the average response time for SF was 600 ms faster than NF. SF is better than NF for position, type, strength, and the overall modality regarding both accuracy and response time except for 1C modality (p<0.001). Among the six modalities of stimulation channels, performance of 1C/SF was the best, which was similar to that of 1C/NF and 3C/SF; performance of 3C/NF was similar to that of 5C/SF; performance of 5C/NF was the worst. NASA-TLX scores indicated that mental workload increased as the number of stimulation channels increased.ConclusionsWe quantified the difference between SF and NF, and the influence of different number of stimulation channels. SF was better than NF in general, but the practical issues such as the limited area of stumps could constrain the use of SF. We found that more channels increased the amount and richness of information to the amputee while fewer channels resulted in higher performance, and thus the 3C/SF modality was a good compromise. Based on this study, we provide possible solutions to the practical problems involving the implementation of tactile feedback for amputees. These results are expected to promote the application of SF and NF tactile feedback for amputees in the future.