Abstract: Wireless sensing for in-vehicle child presence detection is described. In one example, a described method comprises: obtaining a time series of channel information (TSCI) of a wireless channel in a vehicle; computing a motion statistics (MS) based on channel information (CI) of the TSCI in a time period; detecting a motion of a user in the time period by comparing the motion statistics with a first threshold, wherein the motion of the user is detected when the motion statistics exceed the first threshold; constructing a 2-dimensional (2D) transform matrix based on 1-dimensional (1D) transforms of CI of TSCI in sliding time windows in the time period; detecting a number of horizontal streaks of the 2D transform matrix; detecting a breathing motion of the user in the time period based on the number of detected horizontal streaks of the 2D transform matrix and an associated criterion.

Abstract: Methods, apparatus and systems for wireless sensing based on deep learning are described.

Abstract: Methods, apparatus and systems for radio-assisted signal estimation are described. In one example, a described system comprises: a sensor configured to obtain a baseband mixture signal in a venue; a transmitter configured to transmit a first radio signal through a wireless channel of the venue; a receiver configured to receive a second radio signal through the wireless channel; and a processor. The baseband mixture signal comprises a mixture of a first source signal and an additional signal. The first source signal is generated by a first motion of a first object in the venue. The second radio signal differs from the first radio signal due to the wireless channel and at least the first motion of the first object in the venue.

Abstract: Wireless sensing for in-vehicle child presence detection is described. In one example, a described method comprises: obtaining a time series of channel information (TSCI) of a wireless channel in a vehicle; computing a motion statistics (MS) based on channel information (CI) of the TSCI in a time period; detecting a motion of a user in the time period by comparing the motion statistics with a first threshold, wherein the motion of the user is detected when the motion statistics exceed the first threshold; constructing a 2-dimensional (2D) transform matrix based on 1-dimensional (1D) transforms of CI of TSCI in sliding time windows in the time period; detecting a number of horizontal streaks of the 2D transform matrix; detecting a breathing motion of the user in the time period based on the number of detected horizontal streaks of the 2D transform matrix and an associated criterion.

Abstract: Methods, apparatus and systems for radio-based voice activity detection are described. In one example, a described system comprises: a transmitter configured to transmit a radio signal through a wireless channel of a venue; a receiver configured to receive the radio signal through the wireless channel, wherein the wireless channel is impacted by a voice activity of a target voice source in the venue; and a processor. The processor is configured for: computing a time series of channel information (CI) of the wireless channel based on the radio signal, and detecting the voice activity of the target voice source based on the time series of CI (TSCI) of the wireless channel, without using any media signal.

Abstract: Methods, apparatus and systems for wireless sensing based on linkwise motion statistics (link-MS) are described.

Abstract: The present invention provides a statistical acoustic sensing (SAS)-based method and system for in-vehicle Child Presence Detection. The SAS-based method comprises: transmitting acoustic signal to a subject in a vehicle cabin; receiving acoustic multipath signals scattered by the subject; and processing the acoustic multipath signals to detect presence of the subject by: extracting a plurality of channel impulse response (CIR) data from the received acoustic multipath signals; aggregating the extracted CIR data to estimate acoustic channel state information (CSI); obtaining an autocorrelation function (ACF) of the acoustic CSI based on a statistical acoustic sensing (SAS) model; and performing motion detection and breath tracking on basis of the ACF to detect presence of the subject in the vehicle cabin. The present invention can leverage in-car audio systems to detect presence of young children including newborns in an accurate and responsive manner.

Abstract: Methods, apparatus and systems for map reconstruction based on wireless tracking are described. In one example, a described system comprises: a sensor configured to collect sensing data in a venue and obtain a plurality of trajectories, and a processor. Each trajectory is a time series of spatial coordinates (TSSC) representing a path traversed by a respective object in the venue. Each TSSC is accompanied by at least one respective time series of sensing data (TSSD) collected while the respective object traverses the path in the venue. The processor is configured for: segmenting each TSSC and its accompanying at least one TSSD into segments, bundling the plurality of trajectories based on similarity measures between pairs of the segments, fusing the bundled trajectories to generate fused trajectories, computing a shape of the fused trajectories, and generating a map of the venue based on the computed shape.

Abstract: Methods, apparatus and systems for counting and recognizing objects or people based on rhythmic motion monitoring are described. A described method comprises: obtaining N1 time series of channel information (TSCI) of a wireless multipath channel that is impacted by a rhythmic motion of an object in a venue, wherein the N1 TSCI is extracted from a wireless signal transmitted from a transmitter to a receiver through the wireless multipath channel; decomposing each of the N1 TSCI into N2 time series of channel information components (TSCIC), wherein a channel information component (CIC) of each of the N2 TSCIC at a time comprises a respective component of a channel information (CI) of the TSCI at the time, wherein N1 and N2 are positive integers; monitoring the rhythmic motion of the object based on at least one of: the N1*N2 TSCIC and the N1 TSCI.

Abstract: Methods, apparatus and systems for wireless vital sign monitoring are described. In one example, a described system comprises: a transmitter configured to transmit a wireless signal through a wireless channel of a venue; a receiver configured to receive the wireless signal through the wireless channel that is being impacted by an object motion of an object in the venue; and a processor. At least one of the transmitter or the receiver comprises an array of antennas used to transmit or receive the wireless signal. The object motion comprises at least one non-periodic body motion of the object and at least one periodic vital-sign motion of the object.

Abstract: Methods, apparatus and systems for wireless sensing based on deep learning are described.

Abstract: Methods, apparatus and systems for wireless human-nonhuman motion detection are described.

Abstract: Methods, apparatus and systems for wireless gait recognition and rhythmic motion monitoring are described. In one example, a described system comprises: a transmitter, a receiver, and a processor. The transmitter is configured for transmitting a first wireless signal towards an object in a venue through a wireless multipath channel of the venue. The receiver is configured for: receiving a second wireless signal through the wireless multipath channel between the transmitter and the receiver. The second wireless signal differs from the first wireless signal due to the wireless multipath channel which is impacted by a rhythmic motion of the object. The processor is configured for: obtaining a time series of channel information (CI) of the wireless multipath channel based on the second wireless signal, monitoring the rhythmic motion of the object based on the time series of CI (TSCI), and triggering a response action based on a result of the monitoring.

Abstract: Methods, apparatus and systems for wirelessly monitoring a micro motion of an object are described. In one example, a described system comprises: a transmitter configured for transmitting a first wireless signal through a wireless multipath channel of a venue; a receiver configured for receiving a second wireless signal through the wireless multipath channel; and a processor. The second wireless signal differs from the first wireless signal due to the wireless multipath channel and a motion of an object in the venue.

Abstract: Methods, apparatus and systems for radio-based sleep tracking are described. In one example, a described system comprises: a transmitter configured to transmit a first wireless signal through a wireless multipath channel in a venue; a receiver configured to receive a second wireless signal through the wireless multipath channel, wherein the second wireless signal differs from the first wireless signal due to the wireless multipath channel which is impacted by a sleeping motion of an object in the venue; and a processor.

Abstract: Methods, apparatus and systems for movement tracking are described. In one example, a described system comprises: at least one sensor configured to generate at least one sensing information (SI); a memory; a processor communicatively coupled to the memory and the at least one sensor; and a set of instructions stored in the memory.

Abstract: Methods, apparatus and systems for radio-based voice activity detection are described. In one example, a described system comprises: a transmitter configured to transmit a radio signal through a wireless channel of a venue; a receiver configured to receive the radio signal through the wireless channel, wherein the wireless channel is impacted by a voice activity of a target voice source in the venue; and a processor. The processor is configured for: computing a time series of channel information (CI) of the wireless channel based on the radio signal, and detecting the voice activity of the target voice source based on the time series of CI (TSCI) of the wireless channel, without using any media signal.

Abstract: Methods, apparatus and systems for wireless vital sign monitoring are described. In one example, a described system comprises: a transmitter configured to transmit a wireless signal through a wireless channel of a venue; a receiver configured to receive the wireless signal through the wireless channel that is being impacted by an object motion of an object in the venue; and a processor. At least one of the transmitter or the receiver comprises an array of antennas used to transmit or receive the wireless signal. The object motion comprises at least one non-periodic body motion of the object and at least one periodic vital-sign motion of the object.

Abstract: Methods, apparatus and systems for wireless writing tracking are described. In one example, a described system comprises: a transmitter configured for transmitting a first wireless signal through a wireless multipath channel of a venue; a receiver configured for receiving a second wireless signal through the wireless multipath channel; and a processor. The second wireless signal comprises a reflection of the first wireless signal by a tip of a writing instrument in the venue. The processor is configured for: obtaining a time series of channel information (CI) of the wireless multipath channel based on the second wireless signal, wherein each CI comprises at least one of: a channel state information (CSI), channel impulse response (CIR), channel frequency response (CFR), or received signal strength index (RSSI); and tracking a movement of the tip of the writing instrument based on the time series of CI (TSCI).

Abstract: Methods, apparatus and systems for map reconstruction based on wireless tracking are described. In one example, a described system comprises: a sensor configured to collect sensing data in a venue and obtain a plurality of trajectories, and a processor. Each trajectory is a time series of spatial coordinates (TSSC) representing a path traversed by a respective object in the venue. Each TSSC is accompanied by at least one respective time series of sensing data (TSSD) collected while the respective object traverses the path in the venue. The processor is configured for: segmenting each TSSC and its accompanying at least one TSSD into segments, bundling the plurality of trajectories based on similarity measures between pairs of the segments, fusing the bundled trajectories to generate fused trajectories, computing a shape of the fused trajectories, and generating a map of the venue based on the computed shape.