# CPS: Cyber-physically assistive clothing to reduce societal incident of low back pain

> **NIH NIH R01** · VANDERBILT UNIVERSITY · 2020 · $311,593

## Abstract

The objective of this proposal is to address core scientific challenges related to sensing, actuation and control of
cyber-physically assistive clothing (CPAC). CPAC is a kind of Human-in-the-loop Cyber-Physical System (HCPS), in
which actuated clothing is coordinated in unison with human body movement to enhance safety and health. We
propose addressing key HCPS challenges within the context of using CPAC to reduce societal incidence of low back
pain, by preventing lumbar (spine) overloading and overuse injuries. Low back pain is targeted because it is one of the
leading causes of physical disability and missed work. High and/or repetitive forces on lumbar muscles and discs can
occur during daily tasks, and are known to be major risk factors that can lead to back pain and injury. The long-term
vision is to create smart clothing that can monitor lumbar loading, train safe movement patterns, and directly assist
wearers to reduce the musculoskeletal forces that cause pain and injury. This proposed transformation of clothing is
similar to how wristwatches have transformed from timepieces into health monitors; however, CPAC is even more
exciting because it combines the form-factor of clothing with the assistance benefits of an exoskeleton to reduce
biological tissue loading for a broad range of individuals, occupations and tasks. Thrust 1 will adapt machine learning
techniques in order to monitor lumbar loading and detect excessive spine forces via portable, wearable sensors, such
that timely feedback/intervention can be provided. This thrust will result in the creation of a publicly shared data set
that contains synchronized, multimodal (lab-based and wearable) sensor data collected from >500 actions per
subject, the largest such corpus for machine learning in this domain. Thrust 2 will model the dynamics of cyber,
physical and human components of CPAC in order to develop optimal control and learning strategies. Thrust 3 will
integrate sensors, fusion algorithms and portable actuation into a complete wearable prototype. A human subject
experiment will be performed to objectively evaluate the function of CPAC. At the focus of this proposal is the human
body; monitored, analyzed and assisted by multidisciplinary CPS technologies. The project integrates expertise in
biomechanics, machine learning, sensor fusion, soft robotics, wearable assistive technology, and clinical management
of low back pain to transform clothing from materials that cover the body into wearable systems that can track and
protect low back health. The key scientific HCPS challenges that need to be overcome, and which are addressed in
this proposed research, in order to realize the broad societal benefits of CPAC are: (1) real-time sensing and assistive
control of the HCPS and its co-adaptation to different subjects and diverse environments, (2) system design and
verification ensuring safe operation and that no harm is done to human subjects through unanticipated feedback, (3)
select...

## Key facts

- **NIH application ID:** 9979852
- **Project number:** 5R01EB028105-03
- **Recipient organization:** VANDERBILT UNIVERSITY
- **Principal Investigator:** Karl E Zelik
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $311,593
- **Award type:** 5
- **Project period:** 2018-09-24 → 2022-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9979852

## Citation

> US National Institutes of Health, RePORTER application 9979852, CPS: Cyber-physically assistive clothing to reduce societal incident of low back pain (5R01EB028105-03). Retrieved via AI Analytics 2026-06-10 from https://api.ai-analytics.org/grant/nih/9979852. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*