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Electronic Skin in Robotics and Healthcare: Towards Multimodal Sensing and Intelligent Analysis


Xu, Changhao (2024) Electronic Skin in Robotics and Healthcare: Towards Multimodal Sensing and Intelligent Analysis. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/en0a-ep72.


Skin-interfaced electronics is gradually transforming robotic and medical fields by enabling noninvasive and continuous monitoring of physiological and biochemical information. Despite their promise, current wearable technologies face challenges in several disciplines: Physical sensors are prone to motion-induced noise and lack the capability for effective disease detection, while existing wearable biochemical sensors suffer from operational instability in biofluids, limiting their practicality. Conventional electronic skin contains only a limited category of sensors that are not sufficient for practical applications, and conventional data processing methods for these wearables necessitate manual intervention to filter noise and decipher health-related information.

This thesis presents advances in electronic skin within robotics and healthcare, emphasizing multimodal sensing and data analysis through machine intelligence. Chapter 1 introduces the concept of electronic skin, outlining the emerging sensor technologies and a general machine learning pipeline for data processing. Chapter 2 details the development of multimodal physiological and biochemical sensors that enable long-term continuous monitoring with high sensitivity and stability. Chapter 3 explores the application of integrated electronic skin in robotics, prosthetics, and human machine interactions. Chapter 4 showcases practical implementations of integrated electronic skin with robust sensors for wound monitoring and treatment. Chapter 5 highlights the transformative deployment of artificial intelligence in deconvoluting health profiles on mental health. The last chapter, Chapter 6, delves into the challenges and prospects of artificial intelligence-powered electronic skins, offering predictions for the evolution of smart electronic skins. We envision that multimodal sensing and machine intelligence in electronic skin could significantly advance the field of human machine interactions and personalized healthcare.

Item Type:Thesis (Dissertation (Ph.D.))
Subject Keywords:electronic skin, machine learning, multimodal sensors, robotics, healthcare
Degree Grantor:California Institute of Technology
Division:Engineering and Applied Science
Major Option:Medical Engineering
Minor Option:Computer Science
Thesis Availability:Public (worldwide access)
Research Advisor(s):
  • Gao, Wei
Thesis Committee:
  • Gharib, Morteza (chair)
  • Yue, Yisong
  • Tai, Yu-Chong
  • Gao, Wei
Defense Date:3 January 2024
Funding AgencyGrant Number
National Institutes of Health (NIH)R01HL155815
National Institutes of Health (NIH)R21DK13266
National Science Foundation2145802
Office of Naval Research (ONR)N00014-21-1-2483
Office of Naval Research (ONR)N00014-21-1-2845
Army Research OfficeW911NF-23-1-0041
National Academy of Medicine Catalyst AwardUNSPECIFIED
Tobacco-Related Disease Research Program High Impact Pilot Research AwardT31IP1666
Amazon AI4Science FellowshipUNSPECIFIED
Record Number:CaltechTHESIS:02182024-070645738
Persistent URL:
Related URLs:
URLURL TypeDescription adapted for Ch. 1 and Ch. 6 adapted for Ch. 1 adapted for Ch. 2 and Ch. 5 adapted for Ch. 2 adapted for Ch. 2 and Ch. 4 adapted for Ch. 3
Xu, Changhao0000-0002-6817-3341
Default Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:16297
Deposited By: Changhao Xu
Deposited On:28 Feb 2024 17:09
Last Modified:06 Mar 2024 18:37

Thesis Files

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