CN108108654A - A kind of Freehandhand-drawing track reconstructing method based on multi-channel surface myoelectric signal - Google Patents

A kind of Freehandhand-drawing track reconstructing method based on multi-channel surface myoelectric signal Download PDF

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CN108108654A
CN108108654A CN201710848790.2A CN201710848790A CN108108654A CN 108108654 A CN108108654 A CN 108108654A CN 201710848790 A CN201710848790 A CN 201710848790A CN 108108654 A CN108108654 A CN 108108654A
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freehandhand
muscle
signal
coordinate
represent
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杨钟亮
陈育苗
文杨靓
赵丹
陆玄青
贾淼
石进珍
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Donghua University
National Dong Hwa University
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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F2218/00Aspects of pattern recognition specially adapted for signal processing
    • G06F2218/08Feature extraction
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/24Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/25Bioelectric electrodes therefor
    • A61B5/279Bioelectric electrodes therefor specially adapted for particular uses
    • A61B5/296Bioelectric electrodes therefor specially adapted for particular uses for electromyography [EMG]
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/24Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316Modalities, i.e. specific diagnostic methods
    • A61B5/389Electromyography [EMG]
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/72Signal processing specially adapted for physiological signals or for diagnostic purposes
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/011Arrangements for interaction with the human body, e.g. for user immersion in virtual reality
    • G06F3/015Input arrangements based on nervous system activity detection, e.g. brain waves [EEG] detection, electromyograms [EMG] detection, electrodermal response detection

Abstract

The present invention relates to a kind of Freehandhand-drawing track reconstructing methods based on multi-channel surface myoelectric signal, can reach the effect for rebuilding original plot track.Prediction model in the present invention dynamically reflects muscle movement, the variation with electromyography signal forms direct causality, improves reconstruction precision using coordinate difference rather than original coordinates as object vector;Using the action of thumb muscles started by press button as the trigger action of electromyographic signal collection, using nature;Only with surface electromyogram signal and non-linear horizontal, the ordinate regression model of drawing locus, it is succinct efficient, very big application potential is shown in electromyography signal identification field, there is certain reference significance to the research in the fields such as rehabilitation project, CAD, robot control.

Description

A kind of Freehandhand-drawing track reconstructing method based on multi-channel surface myoelectric signal
Technical field
The present invention relates to electromyography signals to identify field, more particularly to a kind of hand based on multi-channel surface myoelectric signal Paint track reconstructing method.
Background technology
Drawing is the basic skills of the mankind, with the popularization of computer and its peripheral equipment, passes through interactive electronic Board is relatively convenient to paint, and is widely used, but some researchers have found, paints on electronic writing plate and not as good as in paper Upper drawing comes naturally, current computer-aided plotting system inhibits the freedom of design to a certain extent.Many institute's weeks To know, drawing is interaction complicated between nervous system and upper limb nerve muscle activity, therefore, the friendship of electromyography signal driving Mutual technology can be applied to the design of the more accurate interactive digital drawing instrument based on gesture.
Surface electromyogram signal is the electric signal generated due to contraction of muscle of instrument acquisition, by surface electromyogram signal Conversion process, analysis and utilization, can be applied to rehabilitation project, biomedical engineering, robot control, computer graphical sets The man-machine engineering fields such as meter.
Well known electromyography signal identification is relatively fewer currently for the identification of the fine movements such as Freehandhand-drawing, hand-written, and there are more Technological difficulties lead to not realize practical application, in recent years the U.S. have researcher use Kalman filtering and Wiener filtering Method realize from the handwritten numeral of multi-channel surface myoelectric signal reconstruction 0-9.However, currently there has been no researcher's propositions A set of effective Freehandhand-drawing track reconstructing method based on multi-channel surface myoelectric signal.
The content of the invention
The purpose of the present invention is:For deficiency of the existing interactive digital drawing instrument on interaction fluency, using flesh The interaction technique of electric signal driving, proposes a kind of Freehandhand-drawing track reconstructing method.
In order to achieve the above object, the technical scheme is that providing a kind of based on multi-channel surface myoelectric signal Freehandhand-drawing track reconstructing method, which is characterized in that comprise the following steps:
Step 1 establishes basic Freehandhand-drawing shape collection;
Skin site corresponding to step 2, the experiment muscle in subject sticks electrode slice, and experiment muscle includes triggering Muscle and function muscle wherein triggering muscle is mesothenar, judge that function muscle is deltoid muscle, oar for drawing action starting point Wrist and brevis, the triceps muscle of arm, extensor muscle of fingers, musculus flexor carpi radialis, musculus extensor carpi ulnaris and the bicipital muscle of arm are stretched in side, for feature extraction with into The track reconstructing of one step;
Step 3, subject concentrate the secondary basic drawing form of selection one to proceed by Freehandhand-drawing, Freehandhand-drawing from basic Freehandhand-drawing shape During beginning, subject is with the start button of thumb press electronic pen and keeps the action, and the electromyography signal of mesothenar occurs at this time It acutely rises and falls, the starting point of Freehandhand-drawing action is judged by the electromyography signal passage, and trigger seven corresponding with function muscle and lead to The electromyography signal in road effectively records;
Step 4, in drawing process, the starting point that Freehandhand-drawing acts is set to the starting point of feature extraction, it is hereafter continuous per Ams The surface electromyogram signal of function muscle is extracted, a myoelectricity root-mean-square value is calculated according to the surface electromyogram signal of every Ams As characteristic value;
Characteristic value is substituted into myoelectricity Freehandhand-drawing track reconstructing model by step 5, is correspondingly calculated and is exported Nms on horizontal, ordinate Front and rear reconstruction coordinate difference, wherein, the acquisition methods of the myoelectricity Freehandhand-drawing track reconstructing model comprise the following steps:
Step 5.1, tracking subject are painted the drawing locus in experiment each time, using Ams for interval collection each moment Under drawing trajectory coordinates, and carry out coordinate form conversion, original coordinates be converted to the form of coordinate difference, the coordinate at i moment It can be expressed as (xi, yi), the coordinate at i-1 moment can be expressed as (xi-1, yi-1), then the coordinate difference at i moment and i-1 moment (Δxi, Ayi) be calculated as:
Δxi=xi-xi-1, i=1,2,3 ..., n
Δyi=yi-yi-1, i=1,2,3 ..., n
Step 5.2 while collection surface electromyography signal is tracked, therefrom extract characteristic value, during the feature extraction of analysis window Between interval be all Ams, continuous analysis window is adjacent and non-intersect;
Step 5.3, using the feature that the coordinate difference being converted to is extracted as object vector, using in step 5.2 as input to Amount using gene expression programming, establishes horizontal, the non-linear myoelectricity track reconstructing model of ordinate;
Step 6, with (0,0) for coordinate origin, according to the coordinate difference of reconstruction, recursively calculate often by the front and rear each of Ams The prediction coordinate at moment, the final continuous drawing locus to rebuild, when completing, discharges the start button of electronic pen, stops The tracking and acquisition of electromyography signal.
Preferably, in the step 1, basic Freehandhand-drawing shape collection includes 12 kinds of basic single shapes, is respectively straight Line, vertical line, oblique line, backslash, arch, invert shape, circle, ellipse, reversed horizontal line, reversed vertical line, backslash with it is anti- To backslash.
Preferably, in the step 2, before adhesive electrode piece, by the hair of the skin site corresponding to experiment muscle Hair shaves, and uses alcohol wipe skin so that Skin Resistance is controlled within the specific limits, using bipolar method, by two panels surface Electrode slice is placed in parallel along muscle fibre direction of travel, and earth polar is pasted onto near the skin site corresponding to experiment muscle, as ginseng Examine electrode, by meat fiber generate electromyography signal gathered by electrode slice, then by sensor amplify and filter, finally by Coder transitions are passed to computer software for digital signal and are handled, shown and recorded.
Preferably, in the step 3, the starting point of Freehandhand-drawing action is judged using the method for threshold decision, is specifically included Following steps:
When the emg amplitude for triggering mesothenar is more than or equal to B μ V, the peak-peak position hereafter generated in Cms is just set For the starting point of Freehandhand-drawing action.
Preferably, in the step 4, feature extraction, the feature extraction of analysis window are carried out using adjacent windows technology Time interval is all Ams, i.e., the length of analysis window is set to Ams, and step-length is also set to Ams, and continuous analysis window is adjacent and not It is intersecting, pass through formulaRoot-mean-square value is calculated as characteristic value, in formula, RMS represents root-mean-square value, Vi The voltage of ith sample point is represented, N represents the number of sampled point.
Preferably, in the step 5, the abscissa difference at the i moment on abscissa before and after Nms isThen have:
In formula, d1Represent the characteristic value of extensor carpi radialis brevis, d2Represent the characteristic value of extensor muscle of fingers, d3Represent musculus extensor carpi ulnaris Characteristic value, d4Represent the characteristic value of musculus flexor carpi radialis, d5Represent the characteristic value of the triceps muscle of arm, d6Represent the feature of the bicipital muscle of arm Value, d7Represent the characteristic value of deltoid muscle;
The ordinate difference at the i moment on ordinate before and after Nms isThen have:
Preferably, in the step 6, the prediction coordinate at i momentThen have:
In formula,For the prediction coordinate at f-1 moment.
Beneficial effects of the present invention:The interaction technique driven using electromyography signal, multichannel tracking surface electromyogram signal, The Freehandhand-drawing track reconstructing based on multi-channel surface myoelectric signal is realized by six steps, is electromyography signal identification technology Extension, provides a kind of effective channel for the improvement of interactive digital drawing instrument, also rehabilitation project, area of computer aided is set The research in the fields such as meter, robot control has certain reference significance.
Description of the drawings
Fig. 1 is the schematic diagram of six step track reconstructing methods;
Fig. 2 is 12 basic figures involved in experiment;
Fig. 3 A and Fig. 3 B are the muscle paste position of electromyographic electrode;
Fig. 4 electronic pen start buttons position;
Fig. 5 hold a pen drawing posture;
The part Freehandhand-drawing track that Fig. 6 is reconstructed.
Specific embodiment
To be clearer and more comprehensible the present invention, hereby with preferred embodiment, and attached drawing is coordinated to be described in detail below.
The present invention proposes a kind of Freehandhand-drawing track reconstructing method based on multi-channel surface myoelectric signal, as shown in Figure 1, The present invention includes six steps in total, and the specific implementation step of this method is as follows:
1st, suitable subject is selected, five male volunteers has been selected to participate in research in this experiment, all subjects are used to With the right hand, the basic Freehandhand-drawing shape collection that subject's track reconstructing method is applicable in is informed in examination, and requires subject from the form collection In the range of choose basic drawing form and carry out Freehandhand-drawing.12 basic stroke figures have been selected in total, as shown in Fig. 2, these figures Shape is although different, comprising eight directional chain-code basis vectors may be constructed arbitrary complex figure.
2nd, the skin site corresponding to the experiment muscle of receptor sticks electrode slice, and experiment muscle includes triggering muscle and work( Can two class of muscle, wherein triggering muscle is mesothenar, judge that function muscle is stretched for deltoid muscle, oar side for drawing action starting point Seven kinds of wrist and brevis, the triceps muscle of arm, extensor muscle of fingers, musculus flexor carpi radialis, musculus extensor carpi ulnaris and the bicipital muscle of arm, for feature extraction with into Electromyographic electrode is attached on right limb by the track reconstructing of one step, as shown in Fig. 3 A and Fig. 3 B.
3rd, subject with the start button of thumb press electronic pen and keeps the action, at this time the electromyography signal of mesothenar Occur acutely to rise and fall, the starting point of Freehandhand-drawing action is judged by the electromyography signal passage, and trigger the myoelectricity of remaining seven passages Signal effectively records, release button when completing, and stops the tracking and acquisition of electromyography signal.The start button position of electronic pen It puts as shown in figure 4, the drawing posture that holds a pen is as shown in Figure 5.
The 4th, the starting point that Freehandhand-drawing acts is set to the starting point of feature extraction, be hereafter carried out continuously surface electromyogram signal per 50ms Extraction, the electromyography signal per 50ms calculate a myoelectricity root-mean-square value as characteristic value;
5th, the surface electromyogram signal root-mean-square value (RMS) of extraction is substituted into myoelectricity Freehandhand-drawing track reconstructing model, correspondingly counted It calculates and exports reconstruction coordinate difference horizontal, on ordinate before and after 50msThe calculation formula of abscissa difference is: In formula, d1Represent the RMS value of extensor carpi radialis brevis, d2Represent the RMS values of extensor muscle of fingers, d3Represent ulnar side The RMS value of wrist protractor, d4Represent the RMS value of musculus flexor carpi radialis, d5Represent the RMS value of the triceps muscle of arm, d6Represent the bicipital muscle of arm RMS value, d7The RMS value of deltoid muscle is represented,Represent the difference of counted abscissa.The calculation formula of ordinate difference is: In formula,Represent counted vertical seat Target difference.
6th, with (0,0) for coordinate origin, according to the coordinate difference of reconstruction, recursively calculate often by 50ms it is front and rear each when The prediction coordinate at quarterSo as to link up into the drawing locus of prediction.
The part Freehandhand-drawing track reconstructed according to above-mentioned six steps according to the figure as shown in fig. 6, can be found that this method This 12 basic single Freehandhand-drawing forms can be effectively reconstructed, the form identification and discrimination rebuild are also higher.
By experimental verification, the present invention can more quickly reconstruct Freehandhand-drawing morph track, Er Qiecao from electromyography signal Make that program is simple, quick and accurate, a new side is provided for the Freehandhand-drawing track reconstructing based on multi-channel surface myoelectric signal Method is laid a good foundation to solve electromyography signal identification with reconstruction.

Claims (7)

  1. A kind of 1. Freehandhand-drawing track reconstructing method based on multi-channel surface myoelectric signal, which is characterized in that comprise the following steps:
    Step 1 establishes basic Freehandhand-drawing shape collection;
    Skin site corresponding to step 2, the experiment muscle in subject sticks electrode slice, experiment muscle include triggering muscle with Function muscle wherein triggering muscle is mesothenar, judges that function muscle is deltoid muscle, wrist is stretched in oar side for drawing action starting point And brevis, the triceps muscle of arm, extensor muscle of fingers, musculus flexor carpi radialis, musculus extensor carpi ulnaris and the bicipital muscle of arm, for feature extraction and further rail Mark is rebuild;
    Step 3, subject concentrate the secondary basic drawing form of selection one to proceed by Freehandhand-drawing from basic Freehandhand-drawing shape, and Freehandhand-drawing starts When, subject is with the start button of thumb press electronic pen and keeps the action, and the electromyography signal of mesothenar occurs violent at this time It rises and falls, the starting point of Freehandhand-drawing action is judged by the electromyography signal passage, and triggers seven passages corresponding with function muscle Electromyography signal effectively records;
    Step 4, in drawing process, the starting point that Freehandhand-drawing acts is set to the starting point of feature extraction, is hereafter carried out continuously and carries per Ams The surface electromyogram signal of function muscle is taken, a myoelectricity root-mean-square value is calculated as special according to the surface electromyogram signal of every Ams Value indicative;
    Characteristic value is substituted into myoelectricity Freehandhand-drawing track reconstructing model by step 5, is correspondingly calculated and is exported on horizontal, ordinate before and after Nms Coordinate difference is rebuild, wherein, the acquisition methods of the myoelectricity Freehandhand-drawing track reconstructing model comprise the following steps:
    Step 5.1, tracking subject are each time painted the drawing locus in experiment, are that interval collection is inscribed when each using Ams It paints trajectory coordinates, and carries out coordinate form conversion, original coordinates are converted to the form of coordinate difference, the coordinate at i moment can be with It is expressed as (xi, yi), the coordinate at i-1 moment can be expressed as (xi-1, yi-1), then coordinate difference (the Δ x at i moment and i-1 momenti, Δyi) be calculated as:
    Δxi=xi-xi-1, i=1,2,3 ..., n
    Δyi=yi-yi-1, i=1,2,3 ..., n
    Step 5.2 while collection surface electromyography signal is tracked, characteristic value is therefrom extracted, between the feature extraction time of analysis window Every being all Ams, continuous analysis window is adjacent and non-intersect;
    Step 5.3, using the coordinate difference being converted to as object vector, using the feature extracted in step 5.2 as input vector, application Gene expression programming establishes horizontal, the non-linear myoelectricity track reconstructing model of ordinate;
    Step 6, with (0,0) for coordinate origin, according to the coordinate difference of reconstruction, recursively calculate often to pass through front and rear each moment of Ams Prediction coordinate, the final continuous drawing locus to rebuild when completing, discharge the start button of electronic pen, stop myoelectricity The tracking and acquisition of signal.
  2. 2. a kind of Freehandhand-drawing track reconstructing method based on multi-channel surface myoelectric signal as described in claim 1, feature exist In in the step 1, basic Freehandhand-drawing shape collection includes 12 kinds of basic single shapes, is respectively straight line, vertical line, oblique line, anti- Oblique line, arch, invert shape, circle, ellipse, reversed horizontal line, reversed vertical line, backslash and reversed backslash.
  3. 3. a kind of Freehandhand-drawing track reconstructing method based on multi-channel surface myoelectric signal as described in claim 1, feature exist In, in the step 2, before adhesive electrode piece, by test muscle corresponding to skin site hair cutting, use wine Smart scrape skin so that Skin Resistance controls within the specific limits, using bipolar method, by two panels surface electrode piece along muscle fibre Direction of travel is placed in parallel, and earth polar is pasted onto near the skin site corresponding to experiment muscle, fine by muscle as with reference to electrode The electromyography signal that dimension generates is gathered by electrode slice, then is amplified and filtered by sensor, is finally number by coder transitions Signal is passed to computer software and is handled, shown and recorded.
  4. 4. a kind of Freehandhand-drawing track reconstructing method based on multi-channel surface myoelectric signal as described in claim 1, feature exist In, in the step 3, using the method for threshold decision judge Freehandhand-drawing action starting point, specifically include following steps:
    When the emg amplitude for triggering mesothenar is more than or equal to B μ V, the peak-peak position hereafter generated in Cms is just set to once The starting point of Freehandhand-drawing action.
  5. 5. a kind of Freehandhand-drawing track reconstructing method based on multi-channel surface myoelectric signal as described in claim 1, feature exist In in the step 4, using the progress feature extraction of adjacent windows technology, the feature extraction time interval of analysis window is all The length of analysis window is set to Ams by Ams, step-length is also set to Ams, and continuous analysis window is adjacent and non-intersect, passes through formulaRoot-mean-square value is calculated as characteristic value, in formula, RMS represents root-mean-square value, ViRepresent ith sample The voltage of point, N represent the number of sampled point.
  6. 6. a kind of Freehandhand-drawing track reconstructing method based on multi-channel surface myoelectric signal as described in claim 1, feature exist In in the step 5, the abscissa difference at the i moment on abscissa before and after Nms isThen have:
    In formula, d1Represent the characteristic value of extensor carpi radialis brevis, d2Represent the characteristic value of extensor muscle of fingers, d3Represent the spy of musculus extensor carpi ulnaris Value indicative, d4Represent the characteristic value of musculus flexor carpi radialis, d5Represent the characteristic value of the triceps muscle of arm, d6Represent the characteristic value of the bicipital muscle of arm, d7 Represent the characteristic value of deltoid muscle;
    The ordinate difference at the i moment on ordinate before and after Nms isThen have:
  7. 7. a kind of Freehandhand-drawing track reconstructing method based on multi-channel surface myoelectric signal as claimed in claim 6, feature exist In, in the step 6, the prediction coordinate at i momentThen have:
    In formula,For the prediction coordinate at i-1 moment.
CN201710848790.2A 2017-09-19 2017-09-19 A kind of Freehandhand-drawing track reconstructing method based on multi-channel surface myoelectric signal Pending CN108108654A (en)

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CN109480838A (en) * 2018-10-18 2019-03-19 北京理工大学 A kind of continuous compound movement Intention Anticipation method of human body based on surface layer electromyography signal
CN109814716A (en) * 2019-01-29 2019-05-28 福州大学 A kind of motion intention coding/decoding method based on dynamic surface electromyography signal
CN110772246A (en) * 2019-09-19 2020-02-11 北京航空航天大学 Device and method for synchronous and apposition detection of bioelectric signals and pressure signals
CN111382778A (en) * 2018-12-29 2020-07-07 达索系统公司 Forming datasets for inferring CAD features of entities
CN111938636A (en) * 2020-07-24 2020-11-17 北京师范大学 Human body electromyographic signal virtual striking vibration feedback system and feedback signal generation method

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Cited By (9)

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Publication number Priority date Publication date Assignee Title
CN109480838A (en) * 2018-10-18 2019-03-19 北京理工大学 A kind of continuous compound movement Intention Anticipation method of human body based on surface layer electromyography signal
CN109480838B (en) * 2018-10-18 2020-09-18 北京理工大学 Human body continuous complex movement intention prediction method based on surface electromyographic signals
CN111382778A (en) * 2018-12-29 2020-07-07 达索系统公司 Forming datasets for inferring CAD features of entities
CN109814716A (en) * 2019-01-29 2019-05-28 福州大学 A kind of motion intention coding/decoding method based on dynamic surface electromyography signal
CN109814716B (en) * 2019-01-29 2021-07-27 福州大学 Movement intention decoding method based on dynamic surface electromyographic signals
CN110772246A (en) * 2019-09-19 2020-02-11 北京航空航天大学 Device and method for synchronous and apposition detection of bioelectric signals and pressure signals
CN110772246B (en) * 2019-09-19 2021-07-30 北京航空航天大学 Device and method for synchronous and apposition detection of bioelectric signals and pressure signals
CN111938636A (en) * 2020-07-24 2020-11-17 北京师范大学 Human body electromyographic signal virtual striking vibration feedback system and feedback signal generation method
CN111938636B (en) * 2020-07-24 2022-03-25 北京师范大学 Human body electromyographic signal virtual striking vibration feedback system and feedback signal generation method

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Application publication date: 20180601