Multi-Person Motion Tracking via RF Body Reflections

Recently, we have witnessed the emergence of technologies that can localize a user and track her gestures based purely on radio reflections off the person's body. These technologies work even if the user is behind a wall or obstruction. However, for these technologies to be fully practical, they need to address major challenges such as scaling to multiple people, accurately localizing them and tracking their gestures, and localizing static users as opposed to requiring the user to move to be detectable. This paper presents WiZ, the first multi-person centimeter-scale motion tracking system that pinpoints people's locations based purely on RF reflections off their bodies. WiZ can also locate static users by sensing minute changes in their RF reflections due to breathing. Further, it can track concurrent gestures made by different individuals, even when they carry no wireless device on them. We implement a prototype of WiZ and show that it can localize up to five users each with a median accuracy of 8-18 cm and 7-11 cm in the x and y dimensions respectively. WiZ can also detect 3D pointing gestures of multiple users with a median orientation error of 8 -16 degrees for each of them. Finally, WiZ can track breathing motion and output the breath count of multiple people with high accuracy

In-home passive monitoring for medical applications

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019Cataloged from PDF version of thesis.Includes bibliographical references (pages 145-161).Recent years have witnessed a surge of in-home monitoring and sensing systems. They promise to change healthcare as we know it by continuously monitoring patients at home. Yet, despite all of the interest and effort that has gone into designing these systems, their capabilities are rudimentary and long term retention rates remain low. One of the main reasons for this is that they require the user to either wear or interact with the sensor in order to work effectively. This thesis addresses many of the challenges faced by systems today enabling novel applications in both in-home monitoring and healthcare. To overcome these challenges, this thesis introduces a novel hardware / software sensor that uses radio signals to enable patient health monitoring at home. It hangs on the wall like a picture frame and transmits low-power radio signals which reflect off of the user and return back to the device. By capturing and processing the reflected signals, physiological metrics related to mobility and vital signs can be extracted without touching the user in any way. Furthermore, it relates these health signals to symptoms of Parkinson Disease by deploying the sensor in a pilot study and comparing the health metrics to gold standard clinical assessments.by Zachary E. Kabelac.Ph. D.Ph.D. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Scienc

3D tracking via body radio reflections

Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2014.Cataloged from PDF version of thesis.Includes bibliographical references (pages 65-66).This thesis presents WiTrack, a system that tracks the 3D motion of a user from the radio signals reflected off her body. It works even if the person is occluded from the WiTrack device or in a different room. WiTrack does not require the user to carry any wireless device, yet its accuracy exceeds current RF localization systems, which require the user to hold a transceiver. Empirical measurements with a WiTrack prototype show that, on average, it localizes the center of a human body to within a median of 10 to 13 cm in the x and y dimensions, and 21 cm in the z dimension. It also provides coarse tracking of body parts, identifying the direction of a pointing hand with a median of 11.2°. WiTrack bridges a gap between RF-based localization systems which locate a user through walls and occlusions, and human-computer interaction systems like Kinect, which can track a user without instrumenting her body, but require the user to stay within the direct line of sight of the device.by Zachary Kabelac.M. Eng

Multi-person localization via RF body reflections

We have recently witnessed the emergence of RF-based indoor localization systems that can track user motion without requiring the user to hold or wear any device. These systems can localize a user and track his gestures by relying solely on the reflections of wireless signals off his body, and work even if the user is behind a wall or obstruction. However, in order for these systems to become practical, they need to address two main challenges: 1) They need to be able to operate in the presence of more than one user in the environment, and 2) they must be able to localize a user without requiring him to move or change his position. This paper presents WiTrack2.0, a multi-person localization system that operates in multipath-rich indoor environments and pinpoints users’ locations based purely on the reflections of wireless signals off their bodies. WiTrack2.0 can even localize static users, and does so by sensing the minute movements due to their breathing.We built a prototype of WiTrack2.0 and evaluated it in a standard office building. Our results show that it can localize up to five people simultaneously with a median accuracy of 11.7 cm in each of the x=y dimensions. Furthermore, WiTrack2.0 provides coarse tracking of body parts, identifying the direction of a pointing hand with a median error of 12.5º, for multiple users in the environment

Wireless Power Hotspot that Charges All of Your Devices

ABSTRACT Each year, consumers carry an increasing number of gadgets on their person: mobile phones, tablets, smartwatches, etc. As a result, users must remember to recharge each device, every day. Wireless charging promises to free users from this burden, allowing devices to remain permanently unplugged. Today's wireless charging, however, is either limited to a single device, or is highly cumbersome, requiring the user to remove all of her wearable and handheld gadgets and place them on a charging pad. This paper introduces MultiSpot, a new wireless charging technology that can charge multiple devices, even as the user is wearing them or carrying them in her pocket. A MultiSpot charger acts as an access point for wireless power. When a user enters the vicinity of the MultiSpot charger, all of her gadgets start to charge automatically. We have prototyped MultiSpot and evaluated it using off-theshelf mobile phones, smartwatches, and tablets. Our results show that MultiSpot can charge 6 devices at distances of up to 50 cm

3D Tracking via Body Radio Reflections

This paper introduces WiTrack, a system that tracks the 3D motion of a user from the radio signals reflected off her body. It works even if the person is occluded from the WiTrack device or in a different room. WiTrack does not require the user to carry any wireless device, yet its accuracy exceeds current RF localization systems, which require the user to hold a transceiver. Empirical measurements with a WiTrack prototype show that, on average, it localizes the center of a human body to within a median of 10 to 13 cm in the x and y dimensions, and 21 cm in the z dimension. It also provides coarse tracking of body parts, identifying the direction of a pointing hand with a median of 11.2°. WiTrack bridges a gap between RF-based localization systems which locate a user through walls and occlusions, and human-computer interaction systems like Kinect, which can track a user without instrumenting her body, but require the user to stay within the direct line of sight of the device.National Science Foundation (U.S.

Smart Homes that Monitor Breathing and Heart Rate

The evolution of ubiquitous sensing technologies has led to intelligent environments that can monitor and react to our daily activities, such as adapting our heating and cooling systems, responding to our gestures, and monitoring our elderly. In this paper, we ask whether it is possible for smart environments to monitor our vital signs remotely, without instrumenting our bodies. We introduce Vital-Radio, a wireless sensing technology that monitors breathing and heart rate without body contact. Vital-Radio exploits the fact that wireless signals are affected by motion in the environment, including chest movements due to inhaling and exhaling and skin vibrations due to heartbeats. We describe the operation of Vital-Radio and demonstrate through a user study that it can track users' breathing and heart rates with a median accuracy of 99%, even when users are 8~meters away from the device, or in a different room. Furthermore, it can monitor the vital signs of multiple people simultaneously. We envision that Vital-Radio can enable smart homes that monitor people's vital signs without body instrumentation, and actively contribute to their inhabitants' well-being.National Science Foundation (U.S.)Microsoft Research (PhD Fellowship

Smart Homes that Monitor Breathing and Heart Rate

The evolution of ubiquitous sensing technologies has led to intelligent environments that can monitor and react to our daily activities, such as adapting our heating and cooling systems, responding to our gestures, and monitoring our elderly. In this paper, we ask whether it is possible for smart environments to monitor our vital signs remotely, without instrumenting our bodies. We introduce Vital-Radio, a wireless sensing technology that monitors breathing and heart rate without body contact. Vital-Radio exploits the fact that wireless signals are affected by motion in the environment, including chest movements due to inhaling and exhaling and skin vibrations due to heartbeats. We describe the operation of Vital-Radio and demonstrate through a user study that it can track users' breathing and heart rates with a median accuracy of 99%, even when users are 8~meters away from the device, or in a different room. Furthermore, it can monitor the vital signs of multiple people simultaneously. We envision that Vital-Radio can enable smart homes that monitor people's vital signs without body instrumentation, and actively contribute to their inhabitants' well-being.National Science Foundation (U.S.)Microsoft Research (PhD Fellowship

Extracting Gait Velocity and Stride Length from Surrounding Radio Signals

© 2017 ACM. Gait velocity and stride length are critical health indicators for older adults. A decade of medical research shows that they provide a predictor of future falls, hospitalization, and functional decline among seniors. However, currently these metrics are measured only occasionally during medical visits. Such infrequent measurements hamper the opportunity to detect changes and intervene early in the impairment process. In this paper, we develop a sensor that uses radio signals to continuously measure gait velocity and stride length at home. Our sensor hangs on a wall like a picture frame. It does not require the monitored person to wear or carry a device on her body. Our approach builds on recent advances in wireless systems which have shown that one can locate people based on how their bodies impact the surrounding radio signals. We demonstrate the accuracy of our method by comparing it to the gold standard in clinical tests, and the VICON motion tracking system. Our experience from deploying the sensor in 14 homes indicates comfort with the technology and a high acceptance rate

Monitoring Behaviors of Patients with Late-stage Dementia Using Passive Environmental Sensing Approaches: A Case Series

OBJECTIVE: To show the feasibility of using different unobtrusive activity-sensing technologies to provide objective behavioral markers of persons with dementia (PwD). DESIGN: Monitored the behaviors of two PwD living in memory care unit using the Oregon Center for Aging & Technology (ORCATECH) platform, and the behaviors of two PwD living in assisted living facility using the Emerald device. SETTING: A memory care unit in Portland, Oregon and an assisted living facility in Framingham, Massachusetts. PARTICIPANTS: A 63-year-old male with Alzheimer's disease (AD), and an 80-year-old female with frontotemporal dementia, both lived in a memory care unit in Portland, Oregon. An 89-year-old woman with a diagnosis of AD, and an 85-year-old woman with a diagnosis of major neurocognitive disorder, Alzheimer's type with behavioral symptoms, both resided at an assisted living facility in Framingham, Massachusetts. MEASUREMENTS: These include: sleep quality measured by the bed pressure mat; number of transitions between spaces and dwell times in different spaces measured by the motion sensors; activity levels measured by the wearable actigraphy device; and couch usage and limb movements measured by the Emerald device. RESULTS: Number of transitions between spaces can identify the patient's episodes of agitation; activity levels correlate well with the patient's excessive level of agitation and lack of movement when the patient received potentially inappropriate medication and neared the end of life; couch usage can detect the patient's increased level of apathy; and periodic limb movements can help detect risperidone-induced side effects. This is the first demonstration that the ORCATECH platform and the Emerald device can measure such activities. CONCLUSION: The use of technologies for monitoring behaviors of PwD can provide more objective and intensive measurements of PwD behaviors