Elizabeth Jacob
Papers
1
Total Citations
4
H-Index
1
About
Elizabeth Jacob is a biomedical engineer whose research focuses on the intersection of human movement analysis, assistive technology, and intelligent signal processing. Her most cited work, "Estimation of Elbow Joint Angle from Surface Electromyogram Signals Using ANFIS" (2019), demonstrates her core contribution: developing adaptive neuro-fuzzy inference systems (ANFIS) to decode muscle activity from surface electromyogram (sEMG) signals for real-time joint angle estimation. This approach holds promise for advancing prosthetics, exoskeletons, and rehabilitation robotics by enabling more natural, intuitive control of assistive devices. With 4 citations to date, her paper has laid groundwork for non-invasive, machine learning-driven interfaces between the human body and external machines. Jacob’s work exemplifies how computational intelligence can bridge the gap between biological signals and mechanical responses, offering a pathway toward smarter, more responsive assistive technologies. Her research is particularly relevant for students and engineers interested in biomedical signal processing, human-robot interaction, and the development of low-cost, wearable systems for motor rehabilitation.
Research Focus
Key Achievements
Top Papers
- 1