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

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
[PAPER] [SLIDES]


Press

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
[WEBSITE] [PAPER] [VIDEO]

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
[WEBSITE] [PAPER]

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
[PAPER] [VIDEO]

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

Smart Homes that Monitor Breathing and Heart Rate
Fadel Adib, Hongzi Mao, Zachary Kabelac, Dina Katabi, Robert C. Miller
ACM CHI 2015
[WEBSITE] [PAPER] [VIDEO1] [VIDEO2]

3D Tracking via Body Radio Reflections
Fadel Adib, Zachary Kabelac, Dina Katabi, Robert C. Miller
Usenix NSDI 2014
[WEBSITE] [PAPER] [VIDEO] [SLIDES]