Wearable dry electrodes are needed for long-term biopotential recordings but are limited by their imperfect compliance with the skin, especially during body movements and sweat secretions, resulting in high interfacial impedance and motion artifacts. Herein, we report an intrinsically conductive polymer dry electrode with excellent self-adhesiveness, stretchability, and conductivity. It shows much lower skin-contact impedance and noise in static and dynamic measurement than the current dry electrodes and standard gel electrodes, enabling to acquire high-quality electrocardiogram (ECG), electromyogram (EMG) and electroencephalogram (EEG) signals in various conditions such as dry and wet skin and during body movement. Hence, this dry electrode can be used for long-term healthcare monitoring in complex daily conditions. We further investigated the capabilities of this electrode in a clinical setting and realized its ability to detect the arrhythmia features of atrial fibrillation accurately, and quantify muscle activity during deep tendon reflex testing and contraction against resistance.

Continuum robots provide inherent structural compliance with high dexterity to access the surgical target sites along tortuous anatomical paths under constrained environments and enable to perform complex and delicate operations through small incisions in minimally invasive surgery. These advantages enable their broad applications with minimal trauma and make challenging clinical procedures possible with miniaturized instrumentation and high curvilinear access capabilities. However, their inherent deformable designs make it difficult to realize 3-D intraoperative real-time shape sensing to accurately model their shape. Solutions to this limitation can lead themselves to further develop closely associated techniques of closed-loop control, path planning, human-robot interaction, and surgical manipulation safety concerns in minimally invasive surgery. Although extensive model-based research that relies on kinematics and mechanics has been performed, accurate shape sensing of continuum robots remains challenging, particularly in cases of unknown and dynamic payloads. This survey investigates the recent advances in alternative emerging techniques for 3-D shape sensing in this field and focuses on the following categories: fiber-optic-sensor-based, electromagnetic-tracking-based, and intraoperative imaging modality-based shape-reconstruction methods. The limitations of existing technologies and prospects of new technologies are also discussed.

There are numerous developments taking place in the field of biorobotics, and one such recent breakthrough is the implementation of soft robots—a pathway to mimic nature’s organic parts for research purposes and in minimally invasive surgeries as a result of their shape-morphing and adaptable features. Hydrogels (biocompatible, biodegradable materials that are used in designing soft robots and sensor integration), have come into demand because of their beneficial properties, such as high water content, flexibility, and multi-faceted advantages particularly in targeted drug delivery, surgery and biorobotics. We illustrate in this review article the different types of biomedical sensors and actuators for which a hydrogel acts as an active primary material, and we elucidate their limitations and the future scope of this material in the nexus of similar biomedical avenues.

Wire-driven flexible robots are efficient devices for minimally invasive surgery, since they can work well in complex and confined environments. However, the real-time positional and shape information of the robot cannot be well estimated, especially when there is an unknown payload or force working on the end effector. In this paper, we propose a novel tip tracking and shape sensing method for wire-driven flexible robots. The proposed method is based on the length of each section of the robot as well as the positional and directional information of the distal end of each section of the robot. For each section, an electromagnetic sensor will be mounted at the distal end to estimate the positional and directional information. A reconstruction algorithm, which is based on a three-order Bézier curve, is carried out utilizing the positional and directional information along with the length information of the section. This method provides the advantage of good tracking results and high shape reconstruction accuracy with limited modification to the robot. Compared with other reconstruction methods, no kinematic model is needed for reconstruction. Therefore, this method works well with an unknown payload that applied at the tip of the robot. The feasibility of the proposed method is verified by simulation and experimental results.

Soft-bodied robots, due to their intrinsic compliance, have shown great potential for operating within unstructured environment and interacting with unknown objects. This letter deals with automatic design and fabrication of soft robots. From a structure point of view, we synthesize a soft cable-driven gripper by recasting its mechanical design as a topology optimization problem. Building on previous work on compliant mechanism optimization, we model the interactions between the gripper and objects more practically, in form of pressure loadings and friction tractions, and furthermore, we investigate how the interaction uncertainties affect the optimization solution by varying the contact location and area. The optimized soft fingers were three-dimensionally printed and then assembled to build a gripper. The experiments show that the gripper can handle a large range of unknown objects of different shapes and weights (up to 1 kg), with different grasping modes. This letter represents an important step toward leveraging the full potential of the freeform design space to generate novel soft-bodied robots.