Electrical Stimulator and Surface Electromyography Integrated Circuits for Musculoskeletal Healthcare
Time: Fri 2024-10-18 10.00
Location: Ka-Sal C (Sven-Olof Öhrvik), Kistagången 16, Kista
Language: English
Subject area: Information and Communication Technology
Doctoral student: Yu-Kai Huang , Elektronik och inbyggda system, Mixed-Signals ICs and Systems
Opponent: Professor Ángel Rodríguez-Vázquez, University of Seville, Sevilla, Spain
Supervisor: Associate Professor Saul Rodriguez, Elektronik och inbyggda system; Professor Ana Rusu, Elektronik och inbyggda system
QC 20240925
Abstract
This thesis presents an innovative approach to the development of a fully integrated multi-channel neuromuscular electrical stimulator (NMES) system and a multi-channel surface electromyography (sEMG) acquisition system for musculoskeletal (MSK) healthcare applications. The main objective is to integrate therapeutic and diagnostic tools into a compact wearable device, enabling closed-loop electrical therapy. By leveraging advancements in semiconductor technology, this thesis explores the implementation of application-specific integrated circuits (ASIC) to combine high-voltage (HV) NMES and low-voltage sEMG signal acquisition circuits on a single chip using a 180 nm bipolar-CMOS-DMOS technology.
The research addresses several key challenges in existing NMES and sEMG systems: the need for a compact, multi-channel NMES device; the need for safe electrical muscular stimulation; the need for spatiotemporal information through multi-channel acquisition; and the need for high channel counts and efficient chip area utilization. To overcome these challenges and advance the NMES technology, this thesis proposes several innovative circuit solutions, including a configurable HV-tolerant multi-channel stimulator, an integrated fail-safe protection circuit, and an inductorless on-chip HV generator. Additionally, channel-sharing techniques for multi-channel biopotential acquisition are comprehensively explored, and a novel frequency-division multiplexed architecture is proposed, featuring low noise, low power consumption, and minimized system complexity.
A significant contribution of this thesis work is the integration of multi-channel NMES and sEMG systems in an ASIC, leading to the development of a real-time embedded system for wearable medical applications. This embedded system incorporates the proposed ASIC for bidirectional interfacing with muscles and an off-the-shelf microcontroller for data acquisition, signal processing, and stimulation pattern control. The proposed system facilitates the continuous collection of vital physiological conditions (e.g., motion intention, contraction force, and fatigue level) of the human muscular system, enabling timely adjustments and interventions via electrical stimulation. In-vivo experimental results showcase its potential to enhance electrical therapy outcomes through closed-loop control and pave the way for improved patient care.