Design of a miniaturized analog front end for wearable devices (wrist-like device)

This project focuses on the design of an analog front end with Photoplethysmography (PPG) and accelerometer (ACC) sensors to be embedded in a wrist device prototype platform that processes the signals in a purely analog fashion for activity detection.
The PPG sensor [1] measures heart activity and it varies with the volume of blood, which in turn varies by the heartbeat. It is based on light (LEDs); specifically, the lower intensity of reflected light indicates a higher volume of blood and vice versa. This signal is very common, and it is in every smartwatch able to measure cardiac activity. In addition, we will integrate into the wrist platform 3 ACCs to detect subjects’ movement and direction. The integration of both PPG and ACC gives an idea of the condition of the subject.
The first novelty is proposed in the fully analog investigation [2]. Each element on the PCB should receive and output an analog signal. This requirement aims at the long-term plan to interface the front end with a neuromorphic mixed-signal chip, like the ones designed at the Institute of Neuroinformatics (UZH/ETHZ).
After the signal condition phase, the system should convert the PPG and ACC into a train of spikes. Different approaches can be investigated, starting from simple thresholding methods to a more complicated asynchronous delta modulation. Once the spikes are generated, they can be streamed outside by using low-power Bluetooth.
At INI we have a test bench for PPG and ACC sensors, Figure 1 to be tested and miniaturized. The testbench board will allow an understanding of the working principle of the sensors, and their requirements to then design a miniaturized PCB that can be integrated into a wrist device prototype, Figure 2. The new PCB should include low-power Bluetooth to stream out PPG and ACC as raw signals and spikes (already generated on the PCB) to the neuromorphic chip where the events are then processed for detecting anomalies in the activity.
The project will give a very comprehensive overview of the analog front end, PCB design, and wearable applications. As the outcome of the project, we expect a 3D-printed bracelet with integrated sensors, that can lead to a patent, and articles in scientific journals/conferences.
The project can be expanded to a master thesis, in case the student is curious to explore the neuromorphic computing of the generated signals.

Bibliography
[1] Park, Junyung, et al. "Photoplethysmogram Analysis and Applications: An Integrative Review." Frontiers in Physiology 12 (2022): 2511.
[2] Pandey, Rajeev Kumar, and Paul C-P. Chao. "An adaptive analog front end for a flexible PPG sensor patch with self-determined motion related DC drift removal." 2021 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE, 2021.

Requirements
Programming skills in Python, knowledge of PCB design, and interest in wearable applications.

Contact
Giacomo Indiveri, giacomo (at) ini.uzh.ch & Elisa Donati, elisa(at)ini.uzh.ch,