Method and apparatus for a gesture controlled interface for wearable devices
Inventors
Wagner, Guy • Langer, Leeor • Dahan, Asher
Assignees
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Publication Number
US-9720515-B2
Publication Date
2017-08-01
Expiration Date
Abstract
A gesture-controlled interface apparatus includes one or a plurality of bio-potential sensors and a processor. The one or a plurality of bio-potential sensors are wearable on a body of a user, for detecting one or a plurality of bio-electrical signals from the body of the user, wherein the one or a plurality of bio-potential sensors include at least one surface nerve conduction (SNC) sensor for detecting at least one surface nerve conduction signal. The processor is configured to compare the detected at least one surface nerve conduction signal with data of a plurality of reference signals corresponding to a plurality of known gestures, each of the reference signals distinctly associated with one of the known gestures, to identify a known gesture from the plurality of known gestures that corresponds to said at least one surface nerve conduction signal, and to communicate the identified known gesture to a computerized device.
Core Innovation
A wearable gesture-controlled interface apparatus includes a strap configured to be worn on a wrist of a user. The strap comprises one or a plurality of bio-potential sensors configured to detect one or a plurality of bio-electrical signals from the wrist, including at least one surface nerve conduction (SNC) sensor for detecting at least one surface nerve conduction signal from nerves in the wrist.
Each detected bio-electrical signal has an amplitude proportional to pressure applied to squeezed fingers, and each detected bio-electrical signal has a frequency proportional to the pressure applied to squeezed fingers. A processor translates the one or a plurality of bio-electrical signals to a pressure control signal proportional to pressure applied to the squeezed fingers and applies the pressure control signal to a computerized device for communication based on the user gesture.
Gesture identification is performed by comparing at least one detected surface nerve conduction signal against a plurality of reference signals corresponding to a plurality of known gestures to identify which known gesture is present. Additional processing includes de-noising, event detection, segmentation, extraction of statistical features, and classification to determine the known gesture.
Claims Coverage
The independent claims are clm-00001 and clm-00013, each centered on translating wrist-detected bio-electrical signals, including at least one surface nerve conduction (SNC) sensor, into a pressure control signal for a computerized device. Across the dependent claims, three additional inventive features appear: frequency proportionality to pressure, SNC-based gesture identification via reference-signal comparison, and an SNC signal-processing pipeline with de-noising, event detection, segmentation, statistical feature extraction, and classification.
Wrist strap with bio-potential sensors including surface nerve conduction sensor
A strap configured to be worn on a wrist of a user comprises one or a plurality of bio-potential sensors for detecting one or a plurality of bio-electrical signals from the wrist, wherein the sensors include at least one surface nerve conduction (SNC) sensor for detecting at least one surface nerve conduction signal from nerves in the wrist.
Amplitude proportional to pressure applied to squeezed fingers
Each detected bio-electrical signal has an amplitude proportional to pressure applied to squeezed fingers.
Pressure control signal translation and application to computerized device
A processor translates the one or a plurality of bio-electrical signals to a pressure control signal proportional to pressure applied to the squeezed fingers and applies the pressure control signal to a computerized device.
Frequency proportional to pressure applied to squeezed fingers
Each detected bio-electrical signal has a frequency proportional to the pressure applied to squeezed fingers.
Comparison of detected SNC signals to reference signals for known gestures
Comparing the detected at least one surface nerve conduction signal to a plurality of reference signals tied to a plurality of known gestures to identify which known gesture is present.
SNC gesture determination pipeline with de-noising, event detection, segmentation, and classification
Denoising at least one detected surface nerve conduction (SNC) signal, detecting an event, segmenting the event into one or more frames, extracting statistical features from the frames, and applying a classification algorithm to determine the known gesture.
The claims cover a wrist strap with bio-potential sensing including at least one SNC sensor, pressure-proportional bio-electrical signals, and translation of those signals into a pressure control signal applied to a computerized device. Additional coverage includes frequency proportionality, SNC-based gesture identification against reference signals, and a processing and classification pipeline for determining a known gesture.
Stated Advantages
Documented Applications
Not explicitly described in patent.
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