Upper limb exosuits (ULEs) are wearable robots that can assist arms to lift or support an object. However, heavy wearable equipment often interferes with the free movement of a person's arms, which have a wide range of motions. This article presents the design and manufacturing processes for a ULE that does not restrict the range of motion of the person wearing it and that can be folded to a small, palm-sized volume for portability. The light and flexible ULE employs a fabric woven from shape memory alloy (SMA) springs (FWS) as an actuator. The FWS uses SMA springs coiled with microdiameter SMA wires, and it exhibits the soft and flexible characteristics of a fabric. The proposed lightweight ULE weighs 540 g and supports the muscular strength for the bending motion of an elbow. The experimental results indicated that the proposed ULE reduced the muscle activity of subjects by approximately 50–70% when they held a load of up to 10 kg under the condition that their temperature was controlled to be 50 °C or lower. This result suggests that the proposed ULE can be used to provide strength assistance for delivery or construction workers.

This study proposes fabric muscles based on shape memory alloy (SMA) springs coiled with a thin diameter SMA wire of 80 μ m to improve heat dissipation under natural convection and forced air cooling. A new structure and its fabrication process are developed to create soft and flexible fabric muscles capable of supplying current and withstanding high external force, using a large number of thin SMA spring bundles. A total of 250 bundles of SMA springs weighing only 3.2 g constitute the fabric muscle that can lift a 1500 times-heavier mass, where each strand behaved like a muscle fiber. The fabric muscle generates a blocking force of up to 56.54 N and a power density of 2072 W kg ⁻¹ . In addition, an air-cooling structure similar to a showerhead is proposed to further improve the actuation speed of the fabric muscles and maintain the flexibility of the fabric muscles. The fabric muscle with forced air cooling is cooled 40.5% faster than that with natural cooling. Finally, the results confirm that forced cooling can drive the muscle with a cycle of 5.5 s.

In the field of robotics, sensors are crucial in enabling the interaction between robots and their users. To ensure this interaction, sensors mainly measure the user’s strength, and based on this, wearable robots are controlled. In this paper, we propose a novel three-axis force/torque sensor for wearable robots that is compact and has a high load capacity. The bolt and nut combination of the proposed sensor is designed to measure high-load weights, and the simple structure of this combination allows the sensor to be compact and light. Additionally, to measure the three-axis force/torque, we design three capacitance-sensing cells. These cells are arranged in parallel to measure the difference in capacitance between the positive and negative electrodes. From the capacitance change measured by these sensing cells, force/torque information is converted through deep neural network calibration. The sensing point can also be confirmed using the geometric and kinematic relation of the sensor. The proposed sensor is manufactured through a simple and inexpensive process using cheap and simply structured components. The performance of the sensor, such as its repeatability and capacity, is evaluated using several experimental setups. In addition, the sensor is applied to a wearable robot to measure the force of an artificial muscle.

This study proposes a soft inductive coil spring (SICS) strain sensor that can measure the strain of soft actuators. The SICS sensor, produced by transforming a shape memory alloy (SMA) wire with the same materials as that of an SMA spring bundle actuator (SSBA) into a coil spring shape, measures inductance changes according to length changes. This study also proposes a manufacturing method, output characteristics of the SICS sensor applicable to the SSBA among soft actuators, and the structure of the SICS sensor-integrated SSBA (SI-SSBA). In the SI-SSBA, the SMA spring bundle and SICS sensor have structures corresponding to the muscle fiber and spindle of the skeletal muscle, respectively. It is demonstrated that when a robotic arm with one degree of freedom is operated by attaching two SI-SSBAs in an antagonistic structure, the displacement of the SSBA can be measured using the proposed strain sensor. The output characteristics of the SICS sensor for the driving speed of the robotic arm were evaluated, and it was experimentally proven that the strain of the SSBA can be stably measured in water under a temperature change of 54 °C from 36 to 90 °C.

Wearable robots require compact sensing interfaces to monitor the forces transmitted through attachment straps. This study aims to combine strap fastening and force measurement in a lightweight buckle, enabling the magnitude and direction of strap loading to be monitored at the attachment interface. The proposed buckle incorporates two capacitive sensing cells and a flexure structure that converts applied loads into measurable capacitance changes. Their combined responses provide dual-axis force sensing within the buckle body. The complete device measures $64\times 45\times 10\mathrm{mm}$ and weighs $34\mathrm{g}$, including its sensing and signal-processing electronics. Its force and angle ranges are 0–$200\mathrm{N}$ and $\pm 8°$, respectively. The average capacitance sensitivity was $1.33\mathrm{fF}/\mathrm{N}$, and the force linearity error was $6.96\%$ of full scale of output (FSO). Force root-mean-square error (RMSE) was $7.34\%$ of FSO without initial preload and $1.21$–$1.76\%$ of FSO with approximately $18\mathrm{N}$ preload in the respective tests. The validation angle RMSE was $1.67\%$ of FSO. Force hysteresis and repeatability were $8.88\%$ and $0.51\%$ of FSO, respectively. The force and angle FSO values were $200\mathrm{N}$ and $16°$. The estimated $-3\mathrm{dB}$ bandwidth was $2.7\mathrm{Hz}$. The proposed design provides a compact sensing interface for strap-based wearable robots.