Methods and devices of multi-functional operating system for care-taking machine

• US 7,963,930 B2
• Filed: 03/11/2009
• Issued: 06/21/2011
• Est. Priority Date: 12/28/2004
• Status: Active Grant

• Current Assignee: Industrial Technology Research Institute
• Original Assignee: Industrial Technology Research Institute
• Inventors: Tu, Mao-Feng, Yeh, Syh-Shiuh, Sun, Chin-Chu
• Primary Examiner(s): HOEKSTRA, JEFFREY GERBEN
• Application Number:
  US12/402,289
• Publication Number:
  US 20090177109A1
• Time in Patent Office: 832 Days
• Field of Search: 600/587, 600/595, 600/372, 600/384, 600/391, 623/24, 623/25
• US Class Current: 600/595
• CPC Class Codes: A61B 2562/0261 Strain gauges
• CPC Class Codes: A61B 2562/046 in a matrix array
• CPC Class Codes: A61B 5/103 Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes A61B5/08 takes precedence; measuring aids for tailors A41H1/00; measuring instruments specially adapted for dentistry A61C19/04
• CPC Class Codes: A61B 5/4519 Muscles A61B5/389, A61B5/224 take precedence

Abstract

The methods and devices of a multi-functional operating interface for a care-taking machine. The multi-functional operating interface of the care-taking machine includes: muscle stretch sensor, multiplexer amplifying wave filter, analog-to-digital signal converter, image processing unit, and muscle pattern database and control bus. Aided by the present muscle template training method and potential image data collecting and processing method, it can become an interface that offers the user of a care-taking machine instantaneous and unlimited controllability of the machine, enabling such people, either sick or handicapped, to enjoy more convenience and better life.

Claims

1. A method for constructing and processing potential images, used to process, analyze, and identify electric signals detected by one or more detecting devices;

said construction and processing method further comprises the following steps;

detecting electric signals by the one or more detecting devices;

processing the electric signals by a multi-task amplifying filter and analog-to-digital converter to form digitized electric signals;

receiving said digital electric signals by an image processing unit;

converting said digital electric signals into grey scale pixel signals to form potential images by the image processing unit;

pre-processing said potential images by highlighting characteristics of said potential images to identify iso-potential lines and iso-potential points via the image processing unit;

grouping said potential images according to their characteristics, and tallying said potential images with the characteristics in a muscle template database by the image processing unit;

generating movement commands, by giving movement commands control bus to conduct various controls of said care-taking machine; and

obtaining a next step, by going back to step of receiving said digital electric signals by the image processing unit and starting a next control cycle.

2. The method for constructing and processing potential images as claimed in claim 1, wherein said step of converting said digital electric signals is done by normalizing irregularly or regularly shaped electric voltage signals into 256 categories and then re-arranging them in grey scaled dot matrix images.

3. The method for constructing and processing potential images as claimed in claim 1, wherein said muscle template database is generated by a muscle template training method, and said muscle template training method comprises the following steps:

defining specific muscle movements and control commands, wherein a trainer communicates with a trainee to define what characteristics of muscle pattern represent what said control commands and then the trainer instructs stimulations to the trainee as to how to stimulate/produce said specific muscle movements as defined; and

generating muscle template data, for generating said electric signals through a muscle stretch sensor by the specific muscle movements;

then processing said electric signals by said image processing unit to highlight the characteristics of said electric signals and producing a set of electric signals with said characteristics; and

then storing said electronic signals with said characteristics of muscle pattern, together with corresponding control commands of said specific muscle movements, are then stored in said muscle template database.