Method, apparatus, and system for wireless motion recognition

Patent metadata

Field	Value
Publication number	US-11953618-B2
Application number	US-202117180766-A
Country	US
Kind code	B2
Filing date	Feb 20, 2021
Priority date	Jul 17, 2015
Publication date	Apr 9, 2024
Grant date	Apr 9, 2024

Abstract

Methods, apparatus and systems for wireless motion recognition 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 that is impacted by a motion of an object in the venue. The processor is configured for: obtaining a time series of channel information (TSCI) of the wireless multipath channel based on the second wireless signal, tracking the motion of the object based on the TSCI to generate a gesture trajectory of the object, and determining a gesture shape based on the gesture trajectory and a plurality of pre-determined gesture shapes.

First claim

We claim:

1. A system for wireless motion recognition, comprising:
a transmitter configured for transmitting a first wireless signal through a wireless multipath channel of a venue; and
a receiver configured for receiving 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 that is impacted by a motion of an object in the venue; and
a processor configured for:
obtaining a time series of channel information (TSCI) of the wireless multipath channel based on the second wireless signal,
computing a plurality of pairwise motion statistics (PMS), each PMS computed based on a respective pair of channel information (CI) of the TSCI,
computing a characteristic function for a sliding time window based on a number of PMS computed based on pairs of CI in the sliding time window,
computing at least one characteristic point of the characteristic function,
computing a turn point and an associated turn angle associated with the sliding time window based on the at least one characteristic point, wherein the turn point is where the object moves from a first straight-line segment into a second straight-line segment during the sliding time window and the associated turn angle is an angle between the first straight-line segment and the second straight-line segment,
generating a gesture trajectory of the object, wherein the gesture trajectory comprises at least one turn point, at least one turn angle, and a series of at least two straight line segments,
wherein
each turn point is where the object moves from a straight-line segment to a next temporally adjacent straight-line segment with a respective turn angle being an angle between the two temporally adjacent straight-line segments,
each characteristic point of the characteristic function comprises one of: a local maximum, a local minimum, a constrained local maximum, a constrained local minimum, a zero-crossing, or any one of the above after a smoothing of the characteristic function, and

determining a gesture shape based on: the series of at least two straight-line segments, the at least one turn angle and the at least one turn point of the generated gesture trajectory, and a plurality of pre-determined gesture shapes.

2. The system of claim 1 , wherein:
the object is a body part of a user;
the user is at least one of: a human being, an animal, a robot, or a movable machine;
the motion comprises a continuous movement of the body part; and
the body part comprises at least one of the following of the user: a hand, a foot, an arm, a leg, a head or a finger.

3. The system of claim 2 , wherein:
during the motion of the object, the user is located at a fixed distance from the transmitter and at a fixed distance from the receiver.

4. The system of claim 1 , wherein:
each of the plurality of pre-determined gesture shapes comprises at least two straight-line segments;
each straight-line segment of the at least two straight-line segments represents a spatially continuous movement along the straight-line segment; and
the plurality of pre-determined gesture shapes are different from each other based on at least one of:
different numbers of straight-line segments in the pre-determined gesture shapes;
different turn angles between two temporally adjacent straight-line segments in the pre-determined gesture shapes, wherein the two temporally adjacent straight-line segments represent a spatially continuous movement from one to the other of the two temporally adjacent straight-line segments;
different numbers of intersection points in the pre-determined gesture shapes, wherein each intersection point is a point at an intersection between two temporally non-adjacent straight-line segments; or
different locations of the intersection points in the pre-determined gesture shapes.

5. The system of claim 4 , wherein the processor is further configured for:
for each of the plurality of pre-determined gesture shapes, computing a corresponding matching probability that the gesture trajectory matches the pre-determined gesture shape, to determine a plurality of matching probabilities; and
identifying one of the plurality of pre-determined gesture shapes, wherein a matching probability that the gesture trajectory matches the identified gesture shape is a maximum matching probability among the plurality of matching probabilities.

6. The system of claim 5 , wherein the processor is further configured for:
comparing the maximum matching probability with a threshold;
when the maximum matching probability is larger than the threshold,
recognizing the gesture shape as the identified gesture shape, and
automatically controlling an operation of a device based on the recognized gesture shape; and

when the maximum matching probability is not larger than the threshold, determining the gesture shape as an unknown gesture shape.

7. The system of claim 5 , wherein the processor is further configured for:
for each of the plurality of pre-determined gesture shapes,
computing a first probability that the gesture trajectory has the same number of straight-line segments as the pre-determined gesture shape,
computing a second probability that the gesture trajectory has the same turn angle between two temporally adjacent straight-line segments, which are two straight-line segments sharing a common endpoint, as the pre-determined gesture shape, for each pair of two temporally adjacent straight-line segments in both the gesture trajectory and the pre-determined gesture shape,
computing a third probability that the gesture trajectory has any intersection point of two temporally non-adjacent straight-line segments, which are two straight-line segments not sharing a common endpoint, at the same location as the pre-determined gesture shape, for each pair of two temporally non-adjacent straight-line segments having an intersection point in the pre-determined gesture shape, and
computing the corresponding matching probability based on a product of: the first probability, each second probability and each third probability.

8. The system of claim 7 , wherein the processor is further configured for:
identifying the at least one turn point by determining a first quantity of time instances at which a respective characteristic function reaches a local minimum along the gesture trajectory; and
identifying the series of at least two straight-line segments based on the at least one turn point by estimating a second quantity of straight-line segments in the gesture trajectory based on the first quantity, wherein the first probability is computed based on the second quantity of straight-line segments.

9. The system of claim 8 , wherein the processor is further configured for:
computing an auto-correlation function (ACF) based on the TSCI;
generating a relative speed profile for the motion of the object based on the ACF; and
determining a third quantity of local minima in the relative speed profile, wherein the first quantity of time instances is determined based on the third quantity of local minima.

10. The system of claim 7 , wherein the processor is further configured for:
computing the at least one turn angle associated with the at least one turn point based on a monotonous decay feature of the PMS.

11. The system of claim 10 , wherein:
a first turn point is a common endpoint of a first segment and a temporally adjacent second segment before the first segment;
for each first point on a portion of the first segment, the processor is configured for:
computing a similarity score as the PMS between a first CI corresponding to the first poin

Assignees

• Regani Sai Deepika
• Wang Beibei
• Wu Min
• Liu K J Ray
• Au Oscar Chi Lim
• Origin Res Wireless Inc

Inventors

• Regani Sai Deepika
• Wang Beibei
• Wu Min
• Liu K J Ray
• Au Oscar Chi-Lim

Classifications

• G01S7/415 Primary

  Identification of targets based on measurements of movement associated with the target · CPC title

• G01S13/003

  Bistatic radar systems; Multistatic radar systems · CPC title

• G01S13/86

  Combinations of radar systems with non-radar systems, e.g. sonar, direction finder · CPC title

• G01S7/006

  using shared front-end circuitry, e.g. antennas (G01S13/765, G01S13/825 take precedence) · CPC title

• G01S13/284

  using coded pulses · CPC title