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'.

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.

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.

Real-time position and pose prediction for a self-propelled undulatory swimmer in 3D space with artificial lateral line system.

This study aims to investigate the feasibility of using an artificial lateral line (ALL) system for predicting the real-time position and pose of an undulating swimmer with Carangiform swimming patterns. We established a 3D computational fluid dynamics simulation to replicate the swimming dynamics of a freely swimming mackerel under various motion parameters, calculating the corresponding pressure fields. Using the simulated lateral line data, we trained an artificial neural network to predict the centroid coordinates and orientation of the swimmer. A comprehensive analysis was further conducted to explore the impact of sensor quantity, distribution, noise amplitude and sampling intervals of the ALL array on predicting performance. Additionally, to quantitatively assess the reliability of the localization network, we trained another neural network to evaluate error magnitudes for different input signals. These findings provide valuable insights for guiding future research on mutual sensing and schooling in underwater robotic fish.

Robotic wireless capsule endoscopy: recent advances and upcoming technologies.

Wireless capsule endoscopy (WCE) offers a non-invasive evaluation of the digestive system, eliminating the need for sedation and the risks associated with conventional endoscopic procedures. Its significance lies in diagnosing gastrointestinal tissue irregularities, especially in the small intestine. However, existing commercial WCE devices face limitations, such as the absence of autonomous lesion detection and treatment capabilities. Recent advancements in micro-electromechanical fabrication and computational methods have led to extensive research in sophisticated technology integration into commercial capsule endoscopes, intending to supersede wired endoscopes. This Review discusses the future requirements for intelligent capsule robots, providing a comparative evaluation of various methods' merits and disadvantages, and highlighting recent developments in six technologies relevant to WCE. These include near-field wireless power transmission, magnetic field active drive, ultra-wideband/intrabody communication, hybrid localization, AI-based autonomous lesion detection, and magnetic-controlled diagnosis and treatment. Moreover, we explore the feasibility for future "capsule surgeons".

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.

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.

Evaluating initial usability of a hand augmentation device across a large and diverse sample.

The advancement of motor augmentation and the broader domain of human-machine interaction rely on a seamless integration with users' physical and cognitive capabilities. These considerations may markedly fluctuate among individuals on the basis of their age, form, and abilities. There is a need to develop a standard for considering these diversity needs and preferences to guide technological development, and large-scale testing can provide us with evidence for such considerations. Public engagement events provide an important opportunity to build a bidirectional discourse with potential users for the codevelopment of inclusive and accessible technologies. We exhibited the Third Thumb, a hand augmentation device, at a public engagement event and tested participants from the general public, who are often not involved in such early technological development of wearable robotic technology. We focused on wearability (fit and control), ability to successfully operate the device, and ability levels across diversity factors relevant for physical technologies (gender, handedness, and age). Our inclusive design was successful in 99.3% of our diverse sample of 596 individuals tested (age range from 3 to 96 years). Ninety-eight percent of participants were further able to successfully manipulate objects using the extra thumb during the first minute of use, with no significant influences of gender, handedness, or affinity for hobbies involving the hands. Performance was generally poorer among younger children (aged ≤11 years). Although older and younger adults performed the task comparably, we identified age costs with the older adults. Our findings offer tangible demonstration of the initial usability of the Third Thumb for a broad demographic.

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.

A Tension Sensor Array for Cable-Driven Surgical Robots.

Tendon-sheath structures are commonly utilized to drive surgical robots due to their compact size, flexibility, and straightforward controllability. However, long-distance cable tension estimation poses a significant challenge due to its frictional characteristics affected by complicated factors. This paper proposes a miniature tension sensor array for an endoscopic cable-driven parallel robot, aiming to integrate sensors into the distal end of long and flexible surgical instruments to sense cable tension and alleviate friction between the tendon and sheath. The sensor array, mounted at the distal end of the robot, boasts the advantages of a small size (16 mm outer diameter) and reduced frictional impact. A force compensation strategy was presented and verified on a platform with a single cable and subsequently implemented on the robot. The robot demonstrated good performance in a series of palpation tests, exhibiting a 0.173 N average error in force estimation and a 0.213 N root-mean-square error. In blind tests, all ten participants were able to differentiate between silicone pads with varying hardness through force feedback provided by a haptic device.

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.

A fully autonomous robotic ultrasound system for thyroid scanning.

The current thyroid ultrasound relies heavily on the experience and skills of the sonographer and the expertise of the radiologist, and the process is physically and cognitively exhausting. In this paper, we report a fully autonomous robotic ultrasound system, which is able to scan thyroid regions without human assistance and identify malignant nod- ules. In this system, human skeleton point recognition, reinforcement learning, and force feedback are used to deal with the difficulties in locating thyroid targets. The orientation of the ultrasound probe is adjusted dynamically via Bayesian optimization. Experimental results on human participants demonstrated that this system can perform high-quality ultrasound scans, close to manual scans obtained by clinicians. Additionally, it has the potential to detect thyroid nodules and provide data on nodule characteristics for American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) calculation.

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.

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.

Avian eye-inspired artificial vision takes a step forward.

Bioinspiration from avian eyes allows development of artificial vision systems with foveated and multispectral imaging.