This paper presents multifunctional electronic skin (e-Skin) with a stack of pressure and temperature sensors arrays. The pressure sensor layer comprises of an 8x 8 array of capacitive sensors using soft elastomers as the dielectric medium and the temperature sensing layer comprises of 4 x4 array of conductive polymers based resistive sensors. Three variants of capacitive pressure sensors were developed using two different dielectric materials (PDMS and Ecoflex) to find the best combination of performance and softness. The Ecoflex-based pressure sensor showed high sensitivity (~4.11 kPa ⁻¹ ) at a low-pressure regime (< 1 kPa) and the 7.5:1 PDMS based pressure sensor showed high sensitivity (~2.32 kPa ⁻¹ ) in the high-pressure regime (>1 kPa). Two variants of temperature sensors were fabricated using CNT and CNT & PEDOT:PSS conducting polymer composite and their performance compared. Finally, a highly sensitive CNT+PEDOT:PSS based resistive temperature sensors layer was integrated on top of 7.5:1 PDMS based capacitive pressure sensors layer to realize the e-Skin prototype. The developed e-Skin is capable of sensing pressures greater than 10 kPa with a high sensitivity of ~2.32 kPa ⁻¹ at 1 kPa and temperatures with the sensitivity of ~0.64 (%)/(°C) up to 80°C, thus demonstrating high potential for use in robotics and touch based interactive systems.

This paper presents the design and fabrication of a wearable tactile communication interface with vibrotactile feedback for assistive communication. The interface is based on finger Braille, which is a simple and efficient tactile communication method used by deafblind people. It consists of a flexible piezoresistive sensor and a vibrotactile actuator integrated together and positioned at the index, middle and ring fingers of both hands to represent the six dots of Braille. The sensors were made using flexible piezoresistive material whereas the actuator utilizes electromagnetic principle by means of a flexible coil and a tiny NdFeB permanent magnet. Both were integrated to realize a Bluetooth-enabled tactile communication glove which enables deafblind people to communicate using Braille codes. The evaluation with 20 end-users (10 deafblind and 10 sighted and hearing person) of the tactile interface under standardized conditions demonstrated that users can feel and distinguish the vibration at frequencies ranging from 10Hz to 200Hz which is within the perceivable frequency range for the FA-II receptors. The results show that it took non-experts in Braille within 25s and 55s to send and receive words like “BEST” and “JOURNAL”, with an accuracy of ~75% and 68% respectively.

Highly sensitive capacitive pressure sensors with wide detection range are needed for applications such as human-machine interfaces, electronic skin in robotics, and health monitoring. However, it is challenging to achieve high sensitivity and wide detection range at the same time. Herein, we present an innovative approach to obtain a highly sensitive capacitive pressure sensor by introducing a zinc oxide nanowire (ZnO NW) interlayer at the polydimethylsiloxane (PDMS)/electrodes interface in the conventional metal-insulator-metal architecture. The ZnO NW interlayer significantly enhanced the performance with ~7 times higher sensitivity (from 0.81%kPa ⁻¹ to 5.6452%kPa ⁻¹ at a low-pressure range (0-10 kPa)) with respect to conventional capacitive sensors having PDMS only as the dielectric. The improvement in sensitivity is attributed to the enhanced charge separation and electric dipole generation due to the displacement of Zn ⁺ and O ⁻ under applied pressure. Further, the orientation of ZnO NWs and their placement between the electrodes were investigated which includes either vertical or horizontal NWs near the electrodes, placing a third ZnO NW interlayer in the middle of dielectric PDMS and introducing an air gap between the ZnO NWs/electrode. Among various combinations, the introduction of air gap between the electrode and ZnO NW interlayer revealed a significant improvement in the device performance with ~50 times enhancement at a low-pressure range (0-10 kPa) and more than 200 times increase at a high-pressure range (10-200 kPa), in comparison with the conventional PDMS-based pressure sensor.

This paper presents a tilt sensor comprising of 3D printed capacitive sensors located at the four ends of a ‘+’ shaped channel to provide the orientation of objects by using the capacitive fluid level measurement concept. The interdigitated capacitive sensors were developed by 3D printing and the channel was filled with ecoflex and silicone oil to obtain two variants of tilt sensor. The results show a change in the capacitance of ~11.5% and ~9.53% for ecoflex and silicone oil-based sensors respectively. A drift of ~2.6% is observed for ecoflex and ~0.16% for silicone oil. Considering the lower viscosity and the lower drift, the silicone oil-based tilt sensors were further investigated and two tilt sensors with varying silicone volumes (1 ml and 1.5 ml ) were fabricated and compared for tilt angles ranging from 0° to 30°. The result from all four interdigitated capacitive sensors in the tilt sensing structure show similar rate of change in capacitance (~0.67% per degree increase in the tilt angle) with a standard deviation of ~±0.1%. However, the sensor with higher volume of silicone oil (1.5 ml ) saturated at a tilt angle of ~20° which is ~10° smaller than the response of the sensor fabricated with 1 ml of silicone oil (saturated at 30°). We also demonstrate the possibility of extending the sensor range by optimizing the volume of fluid and the channel’s fluid capacity. With integration of fabricated tilt sensor with a robots’ body, white cane or smart objects etc., it will be possible to obtain the information about orientation.

Medical robotics holds transformative potential for healthcare. Robots excel in tasks requiring precision, including surgery and minimally invasive interventions, and they can enhance diagnostics through improved automated imaging techniques. Despite the application potentials, the adoption of robotics still faces obstacles, such as high costs, technological limitations, regulatory issues, and concerns about patient safety and data security. This roadmap, authored by an international team of experts, critically assesses the state of medical robotics, highlighting existing challenges and emphasizing the need for novel research contributions to improve patient care and clinical outcomes. It explores advancements in machine learning, highlighting the importance of trustworthiness and interpretability in robotics, the development of soft robotics for surgical and rehabilitation applications, and the role of image-guided robotic systems in diagnostics and therapy. Mini, micro, and nano robotics for surgical interventions, as well as rehabilitation and assistive robots, are also discussed. Furthermore, the roadmap addresses service robots in healthcare, covering navigation, logistics, and telemedicine. For each of the topics addressed, current challenges and future directions to improve patient care through medical robotics are suggested.