Behaviroal sensing in homes

Understanding users' behavior at home is central to behavioral, social and mental-health studies. For example:

  • Social researchers are interested in how much time parents spend with their children at homes.
  • Medical professionals would like to know how caregivers interact with a patient.
  • Doctors want to know if a patient has signs of depression or anxiety by understanding how she/he spends time at home.

Current solutions rely on self-reporting (e.g., questionnaires and diaries). However, studies have shown that self-reporting is often inaccurate and subjective, and the large overhead makes users stop reporting in long-term studies. On the other extreme, putting cameras in homes to record everything all the time is accurate but privacy-invasive.


Marko is a tool for enabling behavioral sensing using radio signals. It transmits a low power wireless signal and analyses its reflections from the environment. To answer behavioral related questions, we create an abstraction for behavioral sensing with 3 elements: where, when & how long, and who. The system is designed with three components:

  • Extract short user trajectories from radio reflections (to answer where & when)
  • Tag trajectories with user identities (to answer who)
  • Scale to new users and new homes automatically (for real-world deployments)

It provides a solution that is accurate, low overhead, and non-invasive.

Paper & Slides

Enabling Identification and Behavioral Sensing in Homes using Radio Reflections
Chen-Yu Hsu, Rumen Hristov, Guang-He Lee, Mingmin Zhao, Dina Katabi
ACM CHI Conference on Human Factors in Computing Systems (CHI) 2019


Marko was covered by: World Economic Forum, EurekAlert, India TV, MIT news, and other media outlets.

It has contributed to monitoring COVID-19 patients from a distance (Tech Crunch, Engadget, VentureBeat).

Also check out

Self-Supervised Learning of Appliance Usage
Chen-Yu Hsu, Abbas Zeitoun, Guang-He Lee, Dina Katabi, Tommi Jaakkola
ICLR 2020

Zero-Effort In-Home Sleep and Insomnia Monitoring using Radio Signals
Chen-Yu Hsu, Aayush Ahuja, Shichao Yue, Rumen Hristov, Zachary Kabalec, Dina Katabi
Ubicomp 2017

Extracting Gait Velocity and Stride Length from Surrounding Radio Signals
Chen-Yu Hsu, Yuchen Liu, Zachary Kabelac, Rumen Hristov, Dina Katabi, Christin Liu
CHI 2017

Capturing the Human Figure Through a Wall
Fadel Adib, Chen-Yu Hsu, Hongzi Mao, Dina Katabi, Fredo Durand
SIGGRAPH Asia 2015

Smart Homes that Monitor Breathing and Heart Rate
Fadel Adib, Hongzi Mao, Zachary Kabelac, Dina Katabi, Robert C. Miller
ACM CHI 2015

3D Tracking via Body Radio Reflections
Fadel Adib, Zachary Kabelac, Dina Katabi, Robert C. Miller
Usenix NSDI 2014