Abstract:
Foot drop is the inability to lift the front part of the foot. It happens due to conditions such as stroke,
spinal cord injury, and multiple sclerosis. Functional Electrical Stimulation (FES) can correct foot drop
by applying electrical pulses to targeted nerves. However, most existing FES systems do not properly
balance the electrical charge of these pulses. It is important to apply the electrical pulses only when the
person lifts their foot. A foot sensor is used to detect the foot lift event. However, current sensors use a
cable which creates cable complexity and they are uncomfortable to wear. To address these issues, we
have designed a compact, wireless, charge-balanced, trapezoidal FES system with an Al-driven foot lift
detection system.
The thesis is divided into six chapters. Chapter 1 serves as an introduction, providing an extensive
literature review, defining the problem, and outlining the specific objectives of this research. In Chapter
2, we have discussed the development of the circuit for the FES system. We explored various circuit
designs before finalizing one. This chapter provides a detailed description of all system components,
explaining the process from the initial schematic design to the final PCB layout. We have also presented
the results of our circuit testing and examined the characteristics of the stimulation, particularly focusing
on pulse width and frequency. Chapter 3 focuses on the power management system, detailing how we
effectively supplied power to all components. We have developed positive and negative boost converter
to power the high power amplifier. Chapter 4 focuses on the detection of foot lift in the FES system. It
covers the ethical clearance and the procedures for data collection from patients. This chapter also details
the development of a machine learing algorithm specifically designed for foot lift detection within the
FES system. We trained the model using three different approaches and implemented the final machine
learning model on an ESP32 microcontroller. In Chapter 5, we have discussed the incorporation of all
the subsystems that we have developed in previous chapters. We have also tested the device and
calculated the accuracy. The conclusions and future perspectives of this work have been discussed in
Chapter 6.
