A portable inflatable soft wearable robot to assist the shoulder during industrial work.

Repetitive overhead tasks during factory work can cause shoulder injuries resulting in impaired health and productivity loss. Soft wearable upper extremity robots have the potential to be effective injury prevention tools with minimal restrictions using soft materials and active controls. We present the design and evaluation of a portable inflatable shoulder wearable robot for assisting industrial workers during shoulder-elevated tasks. The robot is worn like a shirt with integrated textile pneumatic actuators, inertial measurement units, and a portable actuation unit. It can provide up to 6.6 newton-meters of torque to support the shoulder and cycle assistance on and off at six times per minute. From human participant evaluations during simulated industrial tasks, the robot reduced agonist muscle activities (anterior, middle, and posterior deltoids and biceps brachii) by up to 40% with slight changes in joint angles of less than 7% range of motion while not increasing antagonistic muscle activity (latissimus dorsi) in current sample size. Comparison of controller parameters further highlighted that higher assistance magnitude and earlier assistance timing resulted in statistically significant muscle activity reductions. During a task circuit with dynamic transitions among the tasks, the kinematics-based controller of the robot showed robustness to misinflations (96% true negative rate and 91% true positive rate), indicating minimal disturbances to the user when assistance was not required. A preliminary evaluation of a pressure modulation profile also highlighted a trade-off between user perception and hardware demands. Finally, five automotive factory workers used the robot in a pilot manufacturing area and provided feedback.

Soft Nanocomposite Based Multi-point, Multi-directional Strain Mapping Sensor Using Anisotropic Electrical Impedance Tomography.

The practical utilization of soft nanocomposites as a strain mapping sensor in tactile sensors and artificial skins requires robustness for various contact conditions as well as low-cost fabrication process for large three dimensional surfaces. In this work, we propose a multi-point and multi-directional strain mapping sensor based on multiwall carbon nanotube (MWCNT)-silicone elastomer nanocomposites and anisotropic electrical impedance tomography (aEIT). Based on the anisotropic resistivity of the sensor, aEIT technique can reconstruct anisotropic resistivity distributions using electrodes around the sensor boundary. This strain mapping sensor successfully estimated stretch displacements (error of 0.54 ± 0.53 mm), surface normal forces (error of 0.61 ± 0.62 N), and multi-point contact locations (error of 1.88 ± 0.95 mm in 30 mm × 30 mm area for a planar shaped sensor and error of 4.80 ± 3.05 mm in 40 mm × 110 mm area for a three dimensional contoured sensor). In addition, the direction of lateral stretch was also identified by reconstructing anisotropic distributions of electrical resistivity. Finally, a soft human-machine interface device was demonstrated as a practical application of the developed sensor.