A Multimodal Assistive-Robotic-Arm Control System to Increase Independence After Tetraplegia.

Following tetraplegia, independence for completing essential daily tasks, such as opening doors and eating, significantly declines. Assistive robotic manipulators (ARMs) could restore independence, but typically input devices for these manipulators require functional use of the hands. We created and validated a hands-free multimodal input system for controlling an ARM in virtual reality using combinations of a gyroscope, eye-tracking, and heterologous surface electromyography (sEMG). These input modalities are mapped to ARM functions based on the user's preferences and to maximize the utility of their residual volitional capabilities following tetraplegia. The two participants in this study with tetraplegia preferred to use the control mapping with sEMG button functions and disliked winking commands. Non-disabled participants were more varied in their preferences and performance, further suggesting that customizability is an advantageous component of the control system. Replacing buttons from a traditional handheld controller with sEMG did not substantively reduce performance. The system provided adequate control to all participants to complete functional tasks in virtual reality such as opening door handles, turning stove dials, eating, and drinking, all of which enable independence and improved quality of life for these individuals.

Bio-inspired multimodal learning with organic neuromorphic electronics for behavioral conditioning in robotics.

Biological systems interact directly with the environment and learn by receiving multimodal feedback via sensory stimuli that shape the formation of internal neuronal representations. Drawing inspiration from biological concepts such as exploration and sensory processing that eventually lead to behavioral conditioning, we present a robotic system handling objects through multimodal learning. A small-scale organic neuromorphic circuit locally integrates and adaptively processes multimodal sensory stimuli, enabling the robot to interact intelligently with its surroundings. The real-time handling of sensory stimuli via low-voltage organic neuromorphic devices with synaptic functionality forms multimodal associative connections that lead to behavioral conditioning, and thus the robot learns to avoid potentially dangerous objects. This work demonstrates that adaptive neuro-inspired circuitry with multifunctional organic materials, can accommodate locally efficient bio-inspired learning for advancing intelligent robotics.

Exoskeleton rehabilitation robot training for balance and lower limb function in sub-acute stroke patients: a pilot, randomized controlled trial.

PURPOSE: This pilot study aimed to investigate the effects of REX exoskeleton rehabilitation robot training on the balance and lower limb function in patients with sub-acute stroke. METHODS: This was a pilot, single-blind, randomized controlled trial. Twenty-four patients with sub-acute stroke (with the course of disease ranging from 3 weeks to 3 months) were randomized into two groups, including a robot group and a control group. Patients in control group received upright bed rehabilitation (n = 12) and those in robot group received exoskeleton rehabilitation robot training (n = 12). The frequency of training in both groups was once a day (60 min each) for 5 days a week for a total of 4 weeks. Besides, the two groups were evaluated before, 2 weeks after and 4 weeks after the intervention, respectively. The primary assessment index was the Berg Balance Scale (BBS), whereas the secondary assessment indexes included the Fugl-Meyer Lower Extremity Motor Function Scale (FMA-LE), the Posture Assessment Scale for Stroke Patients (PASS), the Activities of Daily Living Scale (Modified Barthel Index, MBI), the Tecnobody Balance Tester, and lower extremity muscle surface electromyography (sEMG). RESULTS: The robot group showed significant improvements (P < 0.05) in the primary efficacy index BBS, as well as the secondary efficacy indexes PASS, FMA-LE, MBI, Tecnobody Balance Tester, and sEMG of the lower limb muscles. Besides, there were a significant differences in BBS, PASS, static eye-opening area or dynamic stability limit evaluation indexes between the robotic and control groups (P < 0.05). CONCLUSIONS: This is the first study to investigate the effectiveness of the REX exoskeleton rehabilitation robot in the rehabilitation of patients with stroke. According to our results, the REX exoskeleton rehabilitation robot demonstrated superior potential efficacy in promoting the early recovery of balance and motor functions in patients with sub-acute stroke. Future large-scale randomized controlled studies and follow-up assessments are needed to validate the current findings. CLINICAL TRIALS REGISTRATION: URL: https://www.chictr.org.cn/index.html.Unique identifier: ChiCTR2300068398.

Skin-inspired, sensory robots for electronic implants.

Drawing inspiration from cohesive integration of skeletal muscles and sensory skins in vertebrate animals, we present a design strategy of soft robots, primarily consisting of an electronic skin (e-skin) and an artificial muscle. These robots integrate multifunctional sensing and on-demand actuation into a biocompatible platform using an in-situ solution-based method. They feature biomimetic designs that enable adaptive motions and stress-free contact with tissues, supported by a battery-free wireless module for untethered operation. Demonstrations range from a robotic cuff for detecting blood pressure, to a robotic gripper for tracking bladder volume, an ingestible robot for pH sensing and on-site drug delivery, and a robotic patch for quantifying cardiac function and delivering electrotherapy, highlighting the application versatilities and potentials of the bio-inspired soft robots. Our designs establish a universal strategy with a broad range of sensing and responsive materials, to form integrated soft robots for medical technology and beyond.

Developing the OpenFlexure Microscope towards medical use: technical and social challenges of developing globally accessible hardware for healthcare.

The OpenFlexure Microscope is an accessible, three-dimensional-printed robotic microscope, with sufficient image quality to resolve diagnostic features including parasites and cancerous cells. As access to lab-grade microscopes is a major challenge in global healthcare, the OpenFlexure Microscope has been developed to be manufactured, maintained and used in remote environments, supporting point-of-care diagnosis. The steps taken in transforming the hardware and software from an academic prototype towards an accepted medical device include addressing technical and social challenges, and are key for any innovation targeting improved effectiveness in low-resource healthcare. This article is part of the Theo Murphy meeting issue 'Open, reproducible hardware for microscopy'.

Design and control of jumping microrobots with torque reversal latches.

Jumping microrobots and insects power their impressive leaps through systems of springs and latches. Using springs and latches, rather than motors or muscles, as actuators to power jumps imposes new challenges on controlling the performance of the jump. In this paper, we show how tuning the motor and spring relative to one another in a torque reversal latch can lead to an ability to control jump output, producing either tuneable (variable) or stereotyped jumps. We develop and utilize a simple mathematical model to explore the underlying design, dynamics, and control of a torque reversal mechanism, provides the opportunity to achieve different outcomes through the interaction between geometry, spring properties, and motor voltage. We relate system design and control parameters to performance to guide the design of torque reversal mechanisms for either variable or stereotyped jump performance. We then build a small (356 mg) microrobot and characterize the constituent components (e.g. motor and spring). Through tuning the actuator and spring relative to the geometry of the torque reversal mechanism, we demonstrate that we can achieve jumping microrobots that both jump with different take-off velocities given the actuator input (variable jumping), and those that jump with nearly the same take-off velocity with actuator input (stereotyped jumping). The coupling between spring characteristics and geometry in this system has benefits for resource-limited microrobots, and our work highlights design combinations that have synergistic impacts on output, compared to others that constrain it. This work will guide new design principles for enabling control in resource-limited jumping microrobots.

Implementing a Barcode-Based Whole-Life Cycle Management Process to Improve Robotic Instrument Tracking.

Minimally invasive surgery can involve the use of robotics to improve patient outcomes. Some robotic systems require special instruments with a designated number of uses. In China, during the reprocessing of the robotic instruments, health care personnel determined that the existing tracking processes were inadequate. They conducted a quality improvement project with the goal of establishing a barcode-based standardized process for tracking robotic instruments. They implemented technology that generated a unique identifier each time a robotic instrument was reprocessed after use. Nurses scanned the identifier when surgeons used the instrument. The findings included the increased accuracy of use documentation and decreases in untraceable sterilization and use records, charging concerns, and average daily and monthly inventory times. An increase in adverse event reports associated with robotic instruments also was noted. The use of barcode technology for robotic instrument tracking continues at the facility and may be expanded for additional specialty instruments.

Wearable robots for the real world need vision.

To enhance wearable robots, understanding user intent and environmental perception with novel vision approaches is needed.

A guiding light for stimulating paralyzed muscles.

Improving the performance of closed-loop optogenetic nerve stimulation can reproduce desired muscle activation patterns.

Closed-loop optogenetic neuromodulation enables high-fidelity fatigue-resistant muscle control.

Closed-loop neuroprostheses show promise in restoring motion in individuals with neurological conditions. However, conventional activation strategies based on functional electrical stimulation (FES) fail to accurately modulate muscle force and exhibit rapid fatigue because of their unphysiological recruitment mechanism. Here, we present a closed-loop control framework that leverages physiological force modulation under functional optogenetic stimulation (FOS) to enable high-fidelity muscle control for extended periods of time (>60 minutes) in vivo. We first uncovered the force modulation characteristic of FOS, showing more physiological recruitment and significantly higher modulation ranges (>320%) compared with FES. Second, we developed a neuromuscular model that accurately describes the highly nonlinear dynamics of optogenetically stimulated muscle. Third, on the basis of the optogenetic model, we demonstrated real-time control of muscle force with improved performance and fatigue resistance compared with FES. This work lays the foundation for fatigue-resistant neuroprostheses and optogenetically controlled biohybrid robots with high-fidelity force modulation.

Efficacy of Daoyin combined with lower limb robot as a comprehensive rehabilitation intervention for stroke patients: a randomized controlled trial.

OBJECTIVE: To assess the effectiveness of a comprehensive rehabilitation approach combining Traditional Chinese Medicine Daoyin with lower limb robotics during the recovery phase of stroke patients. METHODS: Stroke patients meeting the specified criteria were randomly assigned to one of four groups using a random number table: Control group, Daoyin group, lower limb robot group (LLR group), and Daoyin and lower limb robot group (DLLR group). Each group received distinct treatments based on conventional rehabilitation training. The treatment duration spanned two weeks with two days of rest per week. Pre- and post-intervention assessments included various scales: Fugl-Meyer Assessment (FMA), Berg balance scale (BBS), Barthel index (BI), Fatigue Scale-14 (FS-14), Pittsburgh sleep quality index (PSQI), Hamilton Anxiety Scale (HAMA), and Hamilton Depression Scale (HAMD). RESULTS: Statistically significant differences were observed in the lower limb function measured by FAM between the Control group (15 ± 5) and the DLLR group (18 ± 5) (P = 0.049). In the Barthel index, a statistically significant difference was noted between the Control group (54 ± 18) and the DLLR group (64 ± 11) (P = 0.041). Additionally, significant differences were found in the Berg balance scale between the Control group (21 ± 10) and the DLLR group (27 ± 8) (P = 0.024), as well as between the Control group (21 ± 10) and the LLR group (26 ± 10) (P = 0.048). CONCLUSION: The findings of this study suggest that the combined use of Daoyin and robotics not only enhances motor function in stroke patients but also has a positive impact on fatigue, sleep quality, and mood. This approach may offer a more effective rehabilitation strategy for stroke patients.

Pillar electrodes embedded in the skeletal muscle tissue for selective stimulation of biohybrid actuators with increased contractile distance.

Electrodes are crucial for controlling the movements of biohybrid robots, but their external placement outside muscle tissue often leads to inefficient and non-selective stimulation of nearby biohybrid actuators. To address this, we propose embedding pillar electrodes within the skeletal muscle tissue, resulting in enhanced contraction of the target muscle without affecting the neighbor tissue with a 4 mm distance. We use finite element method simulations to establish a selectivity model, correlating the VIE(volume integration of electric field intensity within muscle tissue) with actual contractile distances under different amplitudes of electrical pulses. The simulated selective index closely aligns with experimental results, showing the potential of pillar electrodes for effective and selective biohybrid actuator stimulation. In experiments, we validated that the contractile distance and selectivity achieved with these pillar electrodes exceed conventional Au rod electrodes. This innovation has promising implications for building biohybrid robots with densely arranged muscle tissue, ultimately achieving more human-like movements. Additionally, our selectivity model offers valuable predictive tools for assessing electrical stimulation effects with different electrode designs.

Firing feature-driven neural circuits with scalable memristive neurons for robotic obstacle avoidance.

Neural circuits with specific structures and diverse neuronal firing features are the foundation for supporting intelligent tasks in biology and are regarded as the driver for catalyzing next-generation artificial intelligence. Emulating neural circuits in hardware underpins engineering highly efficient neuromorphic chips, however, implementing a firing features-driven functional neural circuit is still an open question. In this work, inspired by avoidance neural circuits of crickets, we construct a spiking feature-driven sensorimotor control neural circuit consisting of three memristive Hodgkin-Huxley neurons. The ascending neurons exhibit mixed tonic spiking and bursting features, which are used for encoding sensing input. Additionally, we innovatively introduce a selective communication scheme in biology to decode mixed firing features using two descending neurons. We proceed to integrate such a neural circuit with a robot for avoidance control and achieve lower latency than conventional platforms. These results provide a foundation for implementing real brain-like systems driven by firing features with memristive neurons and put constructing high-order intelligent machines on the agenda.

Clinical study on the safety and feasibility of AiWalker-K for lower limbs exercise rehabilitation in children with cerebral palsy.

BACKGROUND: Robotic-assisted gait training (RAGT) devices are effective for children with cerebral palsy (CP). Many RAGT devices have been created and put into clinical rehabilitation treatment. Therefore, we aimed to investigate the safety and feasibility of a new RAGT for children with CP. METHODS: This study is a cross-over design with 23 subjects randomly divided into two groups. The occurrence of adverse events and changes in heart rate and blood pressure were recorded during each AiWalker-K training. Additionally, Gross Motor Function Measure-88 (GMFM-88), Pediatric Balance Scale (PBS), 6 Minutes Walking Test (6MWT), Physiological Cost Index, and Edinburgh Visual Gait Score (EVGS) were used to assess treatment, period, carry-over, and follow-up effects in this study. RESULTS: Adverse events included joint pain, skin pain, and injury. Heart rate and blood pressure were higher with the AiWalker-K compared to the rest (P < 0.05), but remained within safe ranges. After combined treatment with AiWalker-K and routine rehabilitation treatment, significant improvements in 6MWT, GMFM-88 D and E, PBS, and EVGS were observed compared to routine rehabilitation treatment alone (P < 0.05). CONCLUSIONS: Under the guidance of experienced medical personnel, AiWalker-K can be used for rehabilitation in children with CP.

Magnetic Microrobot Swarms with Polymeric Hands Catching Bacteria and Microplastics in Water.

The forefront of micro- and nanorobot research involves the development of smart swimming micromachines emulating the complexity of natural systems, such as the swarming and collective behaviors typically observed in animals and microorganisms, for efficient task execution. This study introduces magnetically controlled microrobots that possess polymeric sequestrant "hands" decorating a magnetic core. Under the influence of external magnetic fields, the functionalized magnetic beads dynamically self-assemble from individual microparticles into well-defined rotating planes of diverse dimensions, allowing modulation of their propulsion speed, and exhibiting a collective motion. These mobile microrobotic swarms can actively capture free-swimming bacteria and dispersed microplastics "on-the-fly", thereby cleaning aquatic environments. Unlike conventional methods, these microrobots can be collected from the complex media and can release the captured contaminants in a second vessel in a controllable manner, that is, using ultrasound, offering a sustainable solution for repeated use in decontamination processes. Additionally, the residual water is subjected to UV irradiation to eliminate any remaining bacteria, providing a comprehensive cleaning solution. In summary, this study shows a swarming microrobot design for water decontamination processes.

A wirelessly programmable, skin-integrated thermo-haptic stimulator system for virtual reality.

Sensations of heat and touch produced by receptors in the skin are of essential importance for perceptions of the physical environment, with a particularly powerful role in interpersonal interactions. Advances in technologies for replicating these sensations in a programmable manner have the potential not only to enhance virtual/augmented reality environments but they also hold promise in medical applications for individuals with amputations or impaired sensory function. Engineering challenges are in achieving interfaces with precise spatial resolution, power-efficient operation, wide dynamic range, and fast temporal responses in both thermal and in physical modulation, with forms that can extend over large regions of the body. This paper introduces a wireless, skin-compatible interface for thermo-haptic modulation designed to address some of these challenges, with the ability to deliver programmable patterns of enhanced vibrational displacement and high-speed thermal stimulation. Experimental and computational investigations quantify the thermal and mechanical efficiency of a vertically stacked design layout in the thermo-haptic stimulators that also supports real-time, closed-loop control mechanisms. The platform is effective in conveying thermal and physical information through the skin, as demonstrated in the control of robotic prosthetics and in interactions with pressure/temperature-sensitive touch displays.

Effect of task-oriented training assisted by force feedback hand rehabilitation robot on finger grasping function in stroke patients with hemiplegia: a randomised controlled trial.

BACKGROUND: Over 80% of patients with stroke experience finger grasping dysfunction, affecting independence in activities of daily living and quality of life. In routine training, task-oriented training is usually used for functional hand training, which may improve finger grasping performance after stroke, while augmented therapy may lead to a better treatment outcome. As a new technology-supported training, the hand rehabilitation robot provides opportunities to improve the therapeutic effect by increasing the training intensity. However, most hand rehabilitation robots commonly applied in clinics are based on a passive training mode and lack the sensory feedback function of fingers, which is not conducive to patients completing more accurate grasping movements. A force feedback hand rehabilitation robot can compensate for these defects. However, its clinical efficacy in patients with stroke remains unknown. This study aimed to investigate the effectiveness and added value of a force feedback hand rehabilitation robot combined with task-oriented training in stroke patients with hemiplegia. METHODS: In this single-blinded randomised controlled trial, 44 stroke patients with hemiplegia were randomly divided into experimental (n = 22) and control (n = 22) groups. Both groups received 40 min/day of conventional upper limb rehabilitation training. The experimental group received 20 min/day of task-oriented training assisted by a force feedback rehabilitation robot, and the control group received 20 min/day of task-oriented training assisted by therapists. Training was provided for 4 weeks, 5 times/week. The Fugl-Meyer motor function assessment of the hand part (FMA-Hand), Action Research Arm Test (ARAT), grip strength, Modified Ashworth scale (MAS), range of motion (ROM), Brunnstrom recovery stages of the hand (BRS-H), and Barthel index (BI) were used to evaluate the effect of two groups before and after treatment. RESULTS: Intra-group comparison: In both groups, the FMA-Hand, ARAT, grip strength, AROM, BRS-H, and BI scores after 4 weeks of treatment were significantly higher than those before treatment (p < 0.05), whereas there was no significant difference in finger flexor MAS scores before and after treatment (p > 0.05). Inter-group comparison: After 4 weeks of treatment, the experimental group's FMA-Hand total score, ARAT, grip strength, and AROM were significantly better than those of the control group (p < 0.05). However, there were no statistically significant differences in the scores of each sub-item of the FMA-Hand after Bonferroni correction (p > 0.007). In addition, there were no statistically significant differences in MAS, BRS-H, and BI scores (p > 0.05). CONCLUSION: Hand performance improved in patients with stroke after 4 weeks of task-oriented training. The use of a force feedback hand rehabilitation robot to support task-oriented training showed additional value over conventional task-oriented training in stroke patients with hand dysfunction. CLINICAL TRIAL REGISTRATION INFORMATION: NCT05841108.

Effects of robot-assisted gait training using the Welwalk on gait independence for individuals with hemiparetic stroke: an assessor-blinded, multicenter randomized controlled trial.

BACKGROUND: Gait disorder remains a major challenge for individuals with stroke, affecting their quality of life and increasing the risk of secondary complications. Robot-assisted gait training (RAGT) has emerged as a promising approach for improving gait independence in individuals with stroke. This study aimed to evaluate the effect of RAGT in individuals with subacute hemiparetic stroke using a one-leg assisted gait robot called Welwalk WW-1000. METHODS: An assessor-blinded, multicenter randomized controlled trial was conducted in the convalescent rehabilitation wards of eight hospitals in Japan. Participants with first-ever hemiparetic stroke who could not walk at pre-intervention assessment were randomized to either the Welwalk group, which underwent RAGT with conventional physical therapy, or the control group, which underwent conventional physical therapy alone. Both groups received 80 min of physical therapy per day, 7 days per week, while the Welwalk group received 40 min of RAGT per day, 6 days per week, as part of their physical therapy. The primary outcome was gait independence, as assessed using the Functional Independence Measure Walk Score. RESULTS: A total of 91 participants were enrolled, 85 of whom completed the intervention. As a result, 91 participants, as a full analysis set, and 85, as a per-protocol set, were analyzed. The primary outcome, the cumulative incidence of gait-independent events, was not significantly different between the groups. Subgroup analysis revealed that the interaction between the intervention group and stroke type did not yield significant differences in either the full analysis or per-protocol set. However, although not statistically significant, a discernible trend toward improvement with Welwalk was observed in cases of cerebral infarction for the full analysis and per-protocol sets (HR 4.167 [95%CI 0.914-18.995], p = 0.065, HR 4.443 [95%CI 0.973-20.279], p = 0.054, respectively). CONCLUSIONS: The combination of RAGT using Welwalk and conventional physical therapy was not significantly more effective than conventional physical therapy alone in promoting gait independence in individuals with subacute hemiparetic stroke, although a trend toward earlier gait independence was observed in individuals with cerebral infarction. TRIAL REGISTRATION: This study was registered with the Japan Registry of Clinical Trials ( https://jrct.niph.go.jp ; jRCT 042180078) on March 3, 2019.

Microsaccade-inspired event camera for robotics.

Neuromorphic vision sensors or event cameras have made the visual perception of extremely low reaction time possible, opening new avenues for high-dynamic robotics applications. These event cameras' output is dependent on both motion and texture. However, the event camera fails to capture object edges that are parallel to the camera motion. This is a problem intrinsic to the sensor and therefore challenging to solve algorithmically. Human vision deals with perceptual fading using the active mechanism of small involuntary eye movements, the most prominent ones called microsaccades. By moving the eyes constantly and slightly during fixation, microsaccades can substantially maintain texture stability and persistence. Inspired by microsaccades, we designed an event-based perception system capable of simultaneously maintaining low reaction time and stable texture. In this design, a rotating wedge prism was mounted in front of the aperture of an event camera to redirect light and trigger events. The geometrical optics of the rotating wedge prism allows for algorithmic compensation of the additional rotational motion, resulting in a stable texture appearance and high informational output independent of external motion. The hardware device and software solution are integrated into a system, which we call artificial microsaccade-enhanced event camera (AMI-EV). Benchmark comparisons validated the superior data quality of AMI-EV recordings in scenarios where both standard cameras and event cameras fail to deliver. Various real-world experiments demonstrated the potential of the system to facilitate robotics perception both for low-level and high-level vision tasks.