Measurement of interaction forces distributed across the attachment interface in wearable devices is critical for understanding ergonomic physical human–robot interaction (pHRI). The main challenges in sensorization of pHRI interfaces are (i) capturing the fine nature of force transmission from compliant human tissue onto rigid surfaces in the wearable device and (ii) utilizing a low-cost and easily implementable design that can be adapted for a variety of human interfaces. This paper addresses both challenges and presents a modular sensing panel that uses force-sensing resistors (FSRs) combined with robust electrical and mechanical integration principles that result in a reliable solution for distributed load measurement. The design is demonstrated through an upper-arm cuff, which uses 24 sensing panels, in conjunction with the Harmony exoskeleton. Validation of the design with controlled loading of the sensorized cuff proves the viability of FSRs in an interface sensing solution. Preliminary experiments with a human subject highlight the value of distributed interface force measurement in recognizing the factors that influence ergonomic pHRI and elucidating their effects. The modular design and low cost of the sensing panel lend themselves to extension of this approach for studying ergonomics in a variety of wearable applications with the goal of achieving safe, comfortable, and effective human–robot interaction.

In this paper, we address two of the most important challenges in development and control of assistive hand orthosis. First, supported by experimental results, we present a method to determine an optimal set of grasping poses, essential for grasping daily objects. Second, we present a method for determining the minimal number of surface EMG sensors and their locations to carry out EMG-based intention recognition and to control the assistive device by differentiating between the hand poses.

The viscoelastic properties of human soft tissue influence the nature of interaction at attachment points in wearable devices. Characterizing these properties is especially critical for understanding physical human-robot interaction (pHRI) for exoskeleton design, prosthetics, and similar fields. This paper presents the design and control of a novel actuated indenter for the measurement of human soft tissue properties. The accuracy of position (0.025 mm) and force (111 mN) measurements allows for repeatable and controlled tissue deformation and monitoring at 36 different angular locations (10° increments). Controlled indentation displacement with force feedback is used in three types of applications on a human subject’s forearm. The soft tissue stiffness profile, viscoelastic relaxation behavior, and frequency domain response are measured. The ability to perform multiple characterizations with one indenter device broadens the scope of a human-centered approach to design, modeling, and perception as they relate to pHRI interfaces.