Strain-sensing goniometers, systems and recognition algorithms

• US 6,035,274 A
• Filed: 01/16/1998
• Issued: 03/07/2000
• Est. Priority Date: 10/14/1988
• Status: Expired due to Fees

• Current Assignee: Board of Trustees of the Leland Stanford Junior University (Stanford University)
• Original Assignee: Board of Trustees of the Leland Stanford Junior University (Stanford University)
• Inventors: Kramer, James F., George, William R., Lindener, Peter
• Primary Examiner(s): Hudspeth, David R.
• Assistant Examiner(s): ABEBE, DANIEL DEMELASH
• Application Number:
  US09/008,028
• Time in Patent Office: 781 Days
• Field of Search: 704/271, 704/270, 704/272
• US Class Current: 704/270
• CPC Class Codes: A61B 2562/0261 Strain gauges
• CPC Class Codes: A61B 5/1071 measuring angles, e.g. using goniometers A61B5/1123 takes precedence
• CPC Class Codes: A61B 5/6806 Gloves
• CPC Class Codes: A61B 5/7267 involving training the classification device
• CPC Class Codes: G06F 1/163 Wearable computers, e.g. on a belt
• CPC Class Codes: G06F 3/011 Arrangements for interaction with the human body, e.g. for user immersion in virtual reality blind teaching G09B21/00
• CPC Class Codes: G06F 3/014 Hand-worn input/output arrangements, e.g. data gloves
• CPC Class Codes: G06F 3/016 Input arrangements with force or tactile feedback as computer generated output to the user
• CPC Class Codes: G09B 21/009 Teaching or communicating with deaf persons G09B21/04 takes precedence; deaf and dumb persons G09B21/00
• CPC Class Codes: G09B 21/04 Devices for conversing with the deaf-blind
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients
• CPC Class Codes: Y10S 128/925 Neural network

Abstract

Goniometers are provided having internal compensation employing two opposing variable resistance strain sensing elements separated by a flexible film. The goniometers may be used in sets for detecting complex hinge or joint movements, where patterns of hinge or joint positions may be used to define symbols. Algorithms are provided for parsing values from a system of goniometers in motion having information content.

Claims

1. A communication system comprising:

means for deriving electrical signals indicative of a configuration of a hand fitted with an instrumented glove having a cover material configured to fit on the hand of a wearer, a plurality of goniometers supported by said cover material and positioned to flex with movement of fingers and/or hand and means for electrically connecting said plurality of goniometers to circuitry of the communication system;

computer means for receiving the electrical signals and determining symbols corresponding to hand-poses, said computer means including an adaptive pattern recognition algorithm responsive to hand-state vectors for recognizing hand-poses in hand-space; and

first output means responsive to said computer means for providing an output of symbols recognized by said adaptive pattern recognition algorithm;

wherein the said adaptive pattern recognition algorithm incorporates a tree-structured artificial neural network classifier.

2. The communication system in claim 1, wherein said computer means comprises a computer.

3. The communication system in claim 1, wherein said means for deriving electrical signals comprises an electrical circuit.

4. The communication system in claim 3, wherein said means for deriving electrical signals comprises at least one sensor.

5. A communication system comprising:

a first circuit deriving electrical signals indicative of a configuration of a hand fitted with an instrumented glove having a cover material configured to fit on the hand of a wearer, a plurality of goniometers supported by said cover material and positioned to flex with movement of fingers and hand, and a second circuit for electrically connecting said plurality of goniometers to circuitry of the communication system;

a computer including a microprocessor receiving the electrical signals and determining symbols corresponding to hand-poses, said computer including an adaptive pattern recognition procedure executing in said microprocessor responsive to hand-state vectors for recognizing hand-poses in hand-space; and

an output circuit responsive to said computer and providing an output of symbols recognized by said adaptive pattern recognition procedure;

wherein the said adaptive pattern recognition procedure incorporates a tree-structured artificial neural network classifier.