We aim to create soft health monitoring devices together with advanced computational techniques to capture and decode biosignals comfortably and accurately.
Mechano-acoustic sensing
A human interacts with the environment and others and generates mechano-acoustic (MA) signals that contain critical information about bioactivities. Most of the signals attenuate at the skin-air interface, but epidermal electronics create a path to capture them. We have invented a wearable mechano-acoustic (MA) sensing technique, which is a wireless, soft, skin-mounted electronic system that incorporates MEMS accelerometers with capabilities of recording body kinematics, along with multimodal MA signatures of underlying body processes, similar to those captured with a stethoscope. Our work focuses on engineering the conformal form of mechano-acoustic detection at anatomical positions of interest, especially those hard for conventional wearable devices with rigid, planar form factors to couple to. The aim is to capture a multitude of human-body mechanics to decode human actions or status in high dimensions. We also work on frequency-domain analysis and machine learning approaches to interpret the networked, high-density MA data streams for advanced monitoring modalities, such as in-vivo, constitutive characterizations of tissues and organs. The goal is to investigate broad classes of biomechanical processes and their inference of the underlying functional properties of the mechanical body.
R. Yao, C. Li, D. Zhuo, T. Chen, and X. Ni, "Feature Anchors for Time-Series Sensor-Based Human Activity Recognition,” arXiv:2604.25092 (2026, preprint).
X. Ni, W. Ouyang, H. Jeong, J.T. Kim, A. Tzaveils, A. Mirzazadeh, C. Wu, J.Y. Lee, M. Keller, C.K. Mummidisetty, M. Patel, N. Shawen, J. Huang, H. Chen, S. Ravi, J.K. Chang, K. Lee, Y. Wu, F. Lie, Y.J. Kang, J.U. Kim, L.P. Chamorro, A.R. Banks, A. Bharat, A. Jayaraman, S. Xu*, J.A. Rogers*, "Automated, multiparametric monitoring of respiratory biomarkers and vital signs in clinical and home settings for COVID-19 patients," Proceedings of the National Academy of Sciences (2021)
K. Lee, X. Ni, J.Y. Lee, H. Arafa, D. Pe, S. Xu, R. Avila, M. Irie, J.H. Lee, R.L. Easterlin, D.H. Kim, H.U. Chung, O.O. Olabisi, S. Getaneh, E. Chung, M. Hill, J. Bell, H.K. Jang, C. Liu, J.B. Park, J. Kim, S.B. Kim, S. Mehta, M. Pharr, A. Tzavelis, J.T. Reeder, I. Huang, Y. Deng, Z. Xie*, C.R. Davies*, Y. Huang*, and J.A. Rogers*, "Mechano-acoustic sensing of physiological processes and body motions using soft, wireless devices interfaced to the skin at the suprasternal notch," Nature Biomedical Engineering 4, 148–158 (2020)
Mechano-acoustic-wave sensing
Mechanical and acoustic waves traveling through the body carry information about the mechanical properties of the tissues and organs along their propagation paths. We have developed a wearable mechano-acoustic-wave sensing technique: a wireless, soft, skin-mounted system that actively generates mechanical waves and records their propagation along the skin. Our work focuses on engineering conformal actuator–sensor systems and frequency-domain analysis methods that use surface-wave dispersion to infer the stiffness of subsurface tissues at depths of several centimeters. The device maintains intimate contact during body motion and enables continuous measurements during exercise and other ambulatory activities, overcoming the tethered operation and frequent calibration required by conventional elastography methods. The aim is to transform epidermal electronics from platforms that monitor naturally generated body signals into active mechanical probes of the body. The goal is to enable longitudinal assessment of tissue health, rehabilitation, and disease progression outside conventional imaging facilities.
C. Li, H. Wang, Z. Song, W. Zhang, Y. Pan, Z. Zhao, C. Qiu, K. Yin, M. Han, A.B. Wang, H. Luan, J. Li, W. Yan, S. Chen, H. Shen, T.-L. Liu, S.S.M. Lee, W. Ding, Y. Huang, J.A. Rogers, C. Wu, X. Ni. "Wireless, wearable elastography via mechano-acoustic wave sensing for ambulatory monitoring of tissue stiffness," Science Advances 11, eady0534 (2025).
Conformal shape sensing
The human body continuously changes shape through motion, contact, and physiological activity, yet most wearable devices measure signals only at isolated locations. We are developing skin-like shape-sensing systems that conform to complex, moving surfaces and reconstruct their three-dimensional geometry in real time. By combining soft distributed sensors with mechanics-informed computation, these systems can perceive stretching and bending, even during contact, without relying on cameras or an external line of sight. The aim is to give epidermal electronics a spatial awareness of the body and its interactions. The goal is to enable new capabilities in motion tracking, haptic interfaces, rehabilitation, surgical monitoring, and closed-loop wearable and robotic systems.
K. Yin, S. Im, C. Qiu, Y. Bai, X. Lu, C. Li, J. Yao, and X. Ni, “A skin-like conformal sensor for real-time shape mapping,” arXiv:2605.01170 (2026, preprint).
Wearable ultrasound and photoacoustic imaging
Many important biological processes occur beneath the skin but remain difficult to observe continuously outside conventional imaging facilities. We are developing wearable ultrasound and photoacoustic tomography (PAT) as complementary platforms for real-time, longitudinal imaging of deep-tissue structure and function during natural behavior. Ultrasound can reveal anatomical, mechanical, and functional information, while PAT provides rich physiological contrast associated with blood flow, oxygenation, and other biological processes. By bringing these capabilities into lightweight, skin-conformal forms, our research aims to create new ways to study, diagnose, and monitor health and disease across the brain and body. Our long-term goal is to establish a fundamentally new interface between the human body and wearable imaging technology.
H. Huo, A. DiSpirito, N. Wang, C. Li, S. Moon, C. Qiu, K. Yin, H. Wu, B. Sun, R. Horstmeyer, W. Feng, X. Jiang, X. Ni, J. Yao*. “Flexible ultrasound array for subcortical brain stimulation in humans: a simulation study," npj Acoustics 2, 11 (2026).
Opportunities and future directions
We welcome students, postdoctoral researchers, and collaborators interested in wearable bioelectronics, non-invasive mechanical, acoustic, ultrasound, and photoacoustic imaging, wave mechanics, signal processing, machine learning, neuroengineering, clinical translation, and longitudinal health monitoring. Current questions include how to extract depth-resolved tissue properties from wearable wave measurements, how to create wearable systems that reveal deep-tissue function during natural behavior, how to build interpretable models of multimodal biosignals, and how to validate new sensing modalities in real-world and clinical settings.