Recordation of handwriting and hand movement using electromyography
First Claim
Patent Images
1. A method to record handwriting activity, comprising:
- registering electromyography (EMG) signals from one or more muscles at selected locations proximate the hand during handwriting activity;
wherein the EMG signals are full-wave rectified and band-pass filtered in the range of 0.2-20 HZ;
correlating the EMG signals with hand movement activity;
processing and storing said EMG signals in a memory for the purposes of handwriting recording;
analyzing said EMG signals and providing an output in a digital format; and
generating and providing an output of a correlation between the hand movements during handwriting and the EMG signals;
wherein one or more EMG sensor electrodes are configured to be disposed on a user'"'"'s hand;
wherein the EMG sensors are dry sensors;
wherein the EMG signals are sampled at a number of time lags with temporary time spacing between samples from several hand muscles and in different combinations;
wherein a pattern recognition algorithm consisting of a mathematical algorithm is trained to reconstruct handwriting patterns from the EMG signals;
wherein the mathematical algorithm is expressed by the equation V(t)=b+Σ
r=mnw(τ
)n(t+τ
) +ε
(t);
wherein n(t+τ
) is a vector of input EMG signals at time t and time lag τ
;
V is the parameter of interest at time t;
w(τ
)is a vector of weights for each input at time lag τ
;
b is the y-intercept;
ε
(t) is the residual error;
wherein the equation is solved using linear least square regression;
and wherein the algorithm is trained by adiusting the parameters of the equation until handwriting patterns are reconstructed from the EMG signals.
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Abstract
Handwriting activity is recorded by use of electromyography (EMG) signals detected from muscles at several locations on the hand. The EMG signals are sensed and registered. The sensed signals are processed and stored, after which the signals are analyzed to reconstruct handwriting activity into a digital format. Machine edible text is generated and displayed along with a graphical depiction of the handwriting.
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Citations
11 Claims
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1. A method to record handwriting activity, comprising:
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registering electromyography (EMG) signals from one or more muscles at selected locations proximate the hand during handwriting activity; wherein the EMG signals are full-wave rectified and band-pass filtered in the range of 0.2-20 HZ; correlating the EMG signals with hand movement activity; processing and storing said EMG signals in a memory for the purposes of handwriting recording; analyzing said EMG signals and providing an output in a digital format; and generating and providing an output of a correlation between the hand movements during handwriting and the EMG signals; wherein one or more EMG sensor electrodes are configured to be disposed on a user'"'"'s hand; wherein the EMG sensors are dry sensors; wherein the EMG signals are sampled at a number of time lags with temporary time spacing between samples from several hand muscles and in different combinations; wherein a pattern recognition algorithm consisting of a mathematical algorithm is trained to reconstruct handwriting patterns from the EMG signals; wherein the mathematical algorithm is expressed by the equation V(t)=b+Σ
r=mnw(τ
)n(t+τ
) +ε
(t);wherein n(t+τ
) is a vector of input EMG signals at time t and time lag τ
;V is the parameter of interest at time t; w(τ
)is a vector of weights for each input at time lag τ
;b is the y-intercept; ε
(t) is the residual error;wherein the equation is solved using linear least square regression; and wherein the algorithm is trained by adiusting the parameters of the equation until handwriting patterns are reconstructed from the EMG signals. - View Dependent Claims (2, 10)
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3. A system to record handwriting activity, comprising:
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means for registration of electromyography (EMG) signals from one or more muscles at selected locations proximate the hand during handwriting activity; means for correlating the EMG signals with hand movement activity;
wherein the EMG signals are full-wave rectified and band-pass filtered in the range of 0.2-20 HZ;
means for providing a digital output of a reconstruction of the EMG signals, the output selected from the group consisting of a digital representation of handwritten text, machine editable text, a drawing, and a digital correlation output; and
means for generating a display corresponding to the digital output;wherein one or more EMG sensor electrodes are configured to be disposed on a user'"'"'s hand; wherein the EMG sensors are dry sensors; wherein the EMG signals are sampled at a number of time lags with temporary time spacing between samples from several hand muscles and in different combinations; wherein a pattern recognition algorithm consisting of a mathematical algorithm is trained to reconstruct handwriting patterns from the EMG signals; wherein the mathematical algorithm is expressed by the equation V(t)=b+Σ
τ
=mnw(τ
)n(t+τ
)+ε
(t) ;wherein n(t+τ
) is a vector of input EMG signals at time t and time lag τ
;V is the parameter of interest at time t; w(τ
)is a vector of weights for each input at time lag τ
;b is the y-intercept; ε
(t) is the residual error;wherein the equation is solved using linear least square regression; and wherein the algorithm is trained by adiusting the parameters of the equation until handwriting patterns are reconstructed from the EMG signals. - View Dependent Claims (4, 5, 6, 7, 8)
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9. A handwriting digital reconstruction system, comprising:
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a plurality of electromyography (EMG) sensors configured to be disposed proximate a user'"'"'s hand during handwriting activity, each sensor being configured to transmit a signal representative of a physiological property of the user; a processor; a pattern recognition program operable by the processor to correlate signals representative of a physiological property of the user with hand movement activity of the user; and data storage means storing program instructions that, when implemented by the processor, are configured to provide a digital representation of the user'"'"'s handwriting based on EMG signals transmitted during the handwriting activity; wherein the EMG signals are full-wave rectified and band-pass filtered in the range of 0.2-20 HZ; wherein one or more EMG sensor electrodes are configured to be disposed on a user'"'"'s hand; wherein the EMG sensors are dry sensors; wherein the EMG signals are sampled at a number of time lags with temporary time spacing between samples from several hand muscles and in different combinations; wherein a pattern recognition algorithm consisting of a mathematical algorithm is trained to reconstruct handwriting patterns from the EMG signals; wherein the mathematical algorithm is expressed by the equation V(t)=b+Σ
τ
=mw(τ
)n(t+τ
) +ε
(t);wherein n(t+τ
) is a vector of input EMG signals at time t and time lag τ
;V is the parameter of interest at time t; w(τ
)is a vector of weights for each input at time lag ε
;b is the y-intercept; ε
(t) is the residual error;wherein the equation is solved using linear least square regression; and wherein the algorithm is trained by adiusting the parameters of the equation until handwriting patterns are reconstructed from the EMG signals. - View Dependent Claims (11)
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Specification