Wearable Sensory Apparatus for Real-Time Feedback in Wearable Robotics

Abstract

We describe the Wearable Sensory Apparatus (WSA) System, which has been implemented and verified in accordance with the relevant standards. It comprises the Inertial Measurement Units (IMUs), real-time wireless data transmission over Ultrawideband (UWB), a Master Unit and several IMU dongles forming the Wireless Body Area Network (WBAN). The WSA is designed for, but is not restricted to, wearable robots. The paper focuses on the topology of the communication network, the WSA hardware, and the organization of the WSA firmware. The experimental evaluation of the WSA incorporates the confirmation of the timing using the supply current WSA profile, measurements related to determining the less error prone position of the master device on the backpack, measurements of the quality of the data transfer in a real environment scenario, measurements in the presence of other microwave signals, and an example of raw IMU signals during human walking. Placement of the master device on the top of the backpack was found to be less error prone, with less than 0.02% packet loss for all the IMU devices placed on different body segments. The packet loss did not change significantly in public buildings or on the street. There was no impact of Wi-Fi bands on the WSA data transfer. The WSA hardware and firmware passed conformance testing in a certified lab. Most importantly, the WSA performed reliably in the laboratory and in clinical tests with exoskeletons and prostheses.

Communication Energy Analysis in Soft Robotic and Artificial Skin Covered Structures Using Modified X-Node WBAN Network

“…With Soft and semi-rigid robots, WBAN can be used to monitor robot behavior and general health, with system architecture contains a central device that receives and interprets data from numerous nearby wireless sensor nodes. In WBAN applications, the devices are typically accessible, making battery replacement simple, with a long battery life expectation [23][24].…”

Advances in Data Analysis for Wearable Sensors

“…In particular, they proposed a two-stage adaptive relay selection and power allocation strategy to maximize the achievable data rate while ensuring the service quality. Munih et al [3] developed a Wireless Body Area Network consisting of a master device and wearable nodes composed of inertial measurement units and radio modules for wireless data transmission over ultrawideband. Kim [4] proposed a cascaded bi-and unidirectional long short-term memory-based deep recurrent neural network model for classifying human gait activities according to walking environmental conditions.…”