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Dive into the research topics where Zachary Kabelac is active.

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Featured researches published by Zachary Kabelac.


acm/ieee international conference on mobile computing and networking | 2015

Wireless Power Hotspot that Charges All of Your Devices

Lixin Shi; Zachary Kabelac; Dina Katabi; David J. Perreault

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. Todays 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-the-shelf mobile phones, smartwatches, and tablets. Our results show that MultiSpot can charge 6 devices at distances of up to 50cm.


human factors in computing systems | 2017

Extracting Gait Velocity and Stride Length from Surrounding Radio Signals

Chen-Yu Hsu; Yuchen Liu; Zachary Kabelac; Rumen Hristov; Dina Katabi; Christine K. Liu

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.


acm/ieee international conference on mobile computing and networking | 2014

Demo: real-time breath monitoring using wireless signals

Fadel Adib; Zachary Kabelac; Hongzi Mao; Dina Katabi; Robert C. Miller

This demo presents Vital-Radio, a wireless sensing technology that monitors breathing remotely, without requiring any body contact. Vital-Radio operates by transmitting a low-power wireless signal and monitoring its reflections off the human body. It uses these reflections to track motion associated with breathing, i.e., the chest movements caused by inhaling and exhaling. The demo will enable any person to sit in front of the device and check that it tracks their inhale and exhale process. The person may hold his/her breath and check that the device detects the breath holding event in real-time.


acm special interest group on data communication | 2018

RF-based 3D skeletons

Mingmin Zhao; Yonglong Tian; Hang Zhao; Mohammad Abu Alsheikh; Tianhong Li; Rumen Hristov; Zachary Kabelac; Dina Katabi; Antonio Torralba

This paper introduces RF-Pose3D, the first system that infers 3D human skeletons from RF signals. It requires no sensors on the body, and works with multiple people and across walls and occlusions. Further, it generates dynamic skeletons that follow the people as they move, walk or sit. As such, RF-Pose3D provides a significant leap in RF-based sensing and enables new applications in gaming, healthcare, and smart homes. RF-Pose3D is based on a novel convolutional neural network (CNN) architecture that performs high-dimensional convolutions by decomposing them into low-dimensional operations. This property allows the network to efficiently condense the spatio-temporal information in RF signals. The network first zooms in on the individuals in the scene, and crops the RF signals reflected off each person. For each individual, it localizes and tracks their body parts - head, shoulders, arms, wrists, hip, knees, and feet. Our evaluation results show that RF-Pose3D tracks each keypoint on the human body with an average error of 4.2 cm, 4.0 cm, and 4.9 cm along the X, Y, and Z axes respectively. It maintains this accuracy even in the presence of multiple people, and in new environments that it has not seen in the training set. Demo videos are available at our website: http://rfpose3d.csail.mit.edu.


Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies | 2017

Zero-Effort In-Home Sleep and Insomnia Monitoring using Radio Signals

Chen-Yu Hsu; Aayush Ahuja; Shichao Yue; Rumen Hristov; Zachary Kabelac; Dina Katabi

Insomnia is the most prevalent sleep disorder in the US. In-home insomnia monitoring is important for both diagnosis and treatment. Existing solutions, however, require the user to either maintain a sleep diary or wear a sensor while sleeping. Both can be quite cumbersome. This paper introduces EZ-Sleep, a new approach for monitoring insomnia and sleep. EZ-Sleep has three properties. First, it is zero effort, i.e., it neither requires the user to wear a sensor nor to record any data. It monitors the user remotely by analyzing the radio signals that bounce off her body. Second, it delivers new features unavailable with other devices such as automatically detecting where the user sleeps and her exact bed schedule, while simultaneously monitoring multiple users in different beds. Third, it is highly accurate. Its average error in measuring sleep latency and total sleep time is 4.9 min and 10.3 min, respectively.


Proceedings of the 2015 Workshop on Wireless of the Students, by the Students, & for the Students | 2015

Poster: Wireless Power Hotspot that Charges All of Your Devices

Lixin Shi; Zachary Kabelac; Dina Katabi; David J. Perreault

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. Todays 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-the-shelf mobile phones, smartwatches, and tablets. Our results show that MultiSpot can charge 6 devices at distances of up to 50cm.


networked systems design and implementation | 2014

3D tracking via body radio reflections

Fadel Adib; Zachary Kabelac; Dina Katabi; Robert C. Miller


human factors in computing systems | 2015

Smart Homes that Monitor Breathing and Heart Rate

Fadel Adib; Hongzi Mao; Zachary Kabelac; Dina Katabi; Robert C. Miller


networked systems design and implementation | 2015

Multi-person localization via RF body reflections

Fadel Adib; Zachary Kabelac; Dina Katabi


Archive | 2014

Multi-Person Motion Tracking via RF Body Reflections

Fadel Adib; Zachary Kabelac; Dina Katabi

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Dina Katabi

Massachusetts Institute of Technology

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Fadel Adib

Massachusetts Institute of Technology

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Chen-Yu Hsu

Massachusetts Institute of Technology

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Lixin Shi

Massachusetts Institute of Technology

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Robert C. Miller

Massachusetts Institute of Technology

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Rumen Hristov

Massachusetts Institute of Technology

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David J. Perreault

Massachusetts Institute of Technology

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Hongzi Mao

Massachusetts Institute of Technology

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Aayush Ahuja

Massachusetts Institute of Technology

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Antonio Torralba

Massachusetts Institute of Technology

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