This thesis describes investigation of the dynamic performance of an analog-to-digital converter (ADC) for wireless wearable systems and separately the development of a Python-based application for electromyography (EMG) data acquisition and processing. To assist in the investigation of ADC dynamic performance, a MATLAB implementation of a time-domain sinusoid fitting technique was developed for effective number of bits (ENOB) estimation. Performance of the ADC was measured against power consumption for various resolution and oversampling configurations on Nordic Semiconductor’s nRF52840 system-on-a-chip (SoC). Results showed oversampling to provide a significant improvement in ENOB, though at a substantial relative cost in power consumption. The Python-based application for EMG was developed to facilitate the acquisition, processing, and visualization of biometric data with a user-friendly graphic user interface. The application was developed with a modular design, utilizing object-oriented coding and open-source libraries, to ease future development.

Creator

• Rosenthal, Marc

Colaboradores

• Xinming Huang
• Clancy, Ted
• Ziming Ziming Zhang

Degree

• MS

Publisher

• Worcester Polytechnic Institute

Identifier

• etd-121305

Palavra-chave

• Analog-to-Digital Converter
• Wireless Wearables
• EMG
• nRF52840

Advisor

• Clancy, Ted

Committee

• Xinming Huang
• Ziming Ziming Zhang

Defense date

• 2024-04-18

Year

• 2024

Sponsor

• Dr. Rabeeh Majidi, CEO, OrthoKinetic Track

UN Sustainable Development Goals

• 3 - Good Health and Well-being

Date created

• 2024-04-22

Resource type

• Thesis

Source

• etd-121305

Rights statement

• In Copyright