3. A system to record handwriting activity, comprising: 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=m n w (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.
3. A system to record handwriting activity, comprising: 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=m n w (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. 5. The system of claim 3 wherein: the means for registration of EMG signals comprises at least one sensor, electrode, amplifier, bandpass filter, multiplexer, analog to digital converter, and processing unit; and the means for registration of EMG signals includes a routine to improve signal to noise ratio.