Characterizing a physical capability by motion analysis

A body and ability technology, applied in the field of characterizing body ability through motion analysis, which can solve problems such as lack of, limiting tools and technical program development, and achieve the effect of rapid and relatively automatic management

Active Publication Date: 2012-05-02
艾伦·约瑟夫·泽尔纳
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the wide array and complexity of underlying human motions, the large amount of raw data generated, and especially the lack of useful results that do not require expert interpretation severely limit the program development of tools and techniques in the field

Method used

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  • Characterizing a physical capability by motion analysis
  • Characterizing a physical capability by motion analysis
  • Characterizing a physical capability by motion analysis

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0033] Example 1 - Back Pain Assessment

[0034] In the context of the back pain assessment, a group of subjects with known impairments of varying degrees were tested.

[0035] From a clinical point of view, a comprehensive set of movements to be performed by the subject is prescribed, while a comprehensive set of parameters characterizing those movements is acquired. Figure 1A and 1B A human body 1 and various possible prescribed movements are shown. For example, the subject may be instructed to bend 2 in one or more specific directions, stand up from a sitting position 3 , twist body parts to varying degrees 4 , walk normally, and turn or move various body parts 5 , 6 . The movement can be repeated multiple times. Prescribed exercise may include exercise performed with weight bearing as well as those performed without weight bearing or with varying degrees of weight bearing. Both motions involving a biomechanically open kinetic chain as well as a closed kinetic chain c...

Embodiment 2

[0040] Example 2 - Malingering Assessment

[0041] A second application example, also related to back pain, is a protocol for malfeasance or "real effort" detection. Rather than producing a scaled index of back health, the protocol produces a two-state classification of inauthentic / authentic effort or deceit / non-deception within the stated confidence level. Following the teachings herein, for both actual back pain patients and control subjects, the possible range of motion and measurements of those motions are assumed, and information about those specific factors is measured and analyzed. A premise of this assessment is that chronic back pain will result in a very consistent movement profile when entering the "pain point" while performing the prescribed movement. In other words, if a subject is asked to perform a task that causes back pain, he or she will experience back pain at the same point during exercise each time the task is performed. Also, it is assumed that the su...

Embodiment 3

[0045] Example 3 - Golf Performance Index

[0046] An example of a sports performance consistent with the theory taught herein is a "golf performance indicator." A GPI score is a scale rating of the overall level of performance of golf skill. One way to think about this situation is as a process of transforming data comprising a time series of values ​​representing human motion into providing an objectively meaningful assessment of that person's golf swing rating. When learning new swings, subjects may progress steadily as they acquire new skills, and may in fact produce erratic end results. When training others or self-training, there is value in objectively assessing progress in learning that swipe in ways other than through the end result. It is desirable to determine the overall figure of merit for swing performance based on minimum measurements (for cost reasons, and for inserted measurement instruments to reduce the golfer's burden). The quality factor or grade perf...

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PUM

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Abstract

Motion analysis is used to classify or rate human capability in a physical domain via a minimized movement and data collection protocol producing a discreet, overall figure of merit of the selected physical capability. The minimal protocol is determined by data mining of a more extensive movement and data collection. Protocols are relevant in medical, sports and occupational applications. Kinematic, kinetic, body type, electromyography (EMG), ground Reactive Force (GRF), demographic, and psychological data are encompassed. Resulting protocols are capable of transforming raw data representing specific human motions into an objective rating of a skill or capability related to those motions.

Description

technical field [0001] Embodiments of the present invention include analyzing human movements to rank or rank physical abilities or conditions involving those movements. Background technique [0002] Kinesiology and kinetic measurements have been used to understand human physiology for purposes of diagnosing disease, sports research, and improving sports skills. Motion data has been collected through a number of measurement techniques, including the use of devices attached to the body and the use of cameras that detect the movement of body parts and detect the movement of specific markers on the body. [0003] Professional sports, clinical and research applications of the technology include training elite athletes, predicting the later onset of cerebral palsy symptoms in infants and young children, and tracking improvement throughout a course of treatment. The cost of dynamic body movement and force measurement equipment has decreased and knowledge of biomechanics has incre...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/103A61B5/11
CPCG06F19/3443A61B5/1038A63B2220/807G06F19/3431A63B24/0006A61B5/7264A61B5/1124A63B2220/806A63B2225/50A63B2220/40A63B69/3608A63B2220/51A63B24/0062A61B5/1127G06K9/00335A63B71/0616A63B69/38A63B2220/30A63B2220/10A61B5/7267G01S5/02A63B2220/12G01S5/145G06F1/1626A63B2209/08G16H50/30G16H50/70
Inventor 艾伦·约瑟夫·泽尔纳
Owner 艾伦·约瑟夫·泽尔纳
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