用于EMG传感器的实时信号处理库。查看README.md以查看原始信号与处理后的信号！_C_Python_下载.zip

# EMG Signal Processing Library (graphed signals below!) - This is a specialized real-time signal processing library for EMG signals - This library provides the tools to extract muscle effort information from EMG signals in real time - Most of the algorithms implemented run in constant time with respect to sampling rate - Currently supports the following languages: C, Python  ##### A comparison of a raw EMG input signal vs. processed output signal (sample_frequency_ = 1000, range_ = 0.1, min_EMG_frequency_ = 25, max_EMG_frequency_ = 300, remove_low_frequency_ = HIGH_PASS_FILTER_ON, reference_available_ = REFERENCE_UNAVAILABLE) -------------------------------------------  ##### Another comparison of a raw EMG input signal vs. processed output signal (sample_frequency_ = 1000, range_ = 0.1, min_EMG_frequency_ = 25, max_EMG_frequency_ = 300, remove_low_frequency_ = HIGH_PASS_FILTER_ON, reference_available_ = REFERENCE_UNAVAILABLE) ------------------------------------------- C DOCUMENTATION ------------------------------------------- ### 1) Setting up Copy the following .c and .h files into your working directory: - emg - ecg - peak_to_peak - moving_average - queue This library was developed using the GCC compiler with the -std=c11 option. It is advisable to also use this option for compiling. ### 2) EMG PROCESSING - Use the EMG module to extract muscle effort information from an EMG signal - This is provides the basis for recognizing gestures through EMG signals. For example, the Myo armband recognizes hand gestures by determining how hard each muscle group in the forearm is flexing. - The module processes the EMG signal using the following steps: 1. Filter high frequency noise from signal, and subtract a reference signal from the actual signal if one is provided 2. Filter low frequency noise from signal and normalize signal (if HIGH_PASS_FILTER_ON is specified in the constructor) 3. Frequencies that are low and high frequency noise are determined by the "min_EMG_frequency_" and "max_EMG_frequency_" constructor arguments 4. Rectify the signal 5. Take a moving average of the signal - The resulting filtered signal is indirectly proportional to the effort exerted by the muscle the sensor is attached to. ------------------------------------------- ```c typedef enum { REFERENCE_AVAILABLE, REFERENCE_UNAVAILABLE, HIGH_PASS_FILTER_ON, HIGH_PASS_FILTER_OFF } EMG_OPTIONS; ``` An enum of the options which must be specified to create a new EMG struct. ------------------------------------------- ```c EMG *new_EMG( uint16_t sample_frequency_, float range_, uint16_t min_EMG_frequency_, uint16_t max_EMG_frequency_, EMG_OPTIONS remove_low_frequency_, EMG_OPTIONS reference_available_); ``` The constructor. Returns a pointer to the newly created EMG struct. - sample_frequency_ * The constant frequency of which data will be given to the EMG data structure (frequency in which filter_EMG will be called). * Specified in Hz - range_ * The number of data points used to calculate moving average, specified in number of seconds (0.2-0.5 is a good value for this). * Data points used in moving average = range_ * sample_frequency_ * Note that the greater the range_ value, thr greater the latency of the filter - min_EMG_frequency_ * Components of signals (noise) below this frequency will be removed. * This argument is specified in Hz * A good value for this is 40 - max_EMG_frequency_ * Components of signals (noise) above this frequnecy will not be accounted for * This is also used in the peak to peak calculations which help remove low frequency noise. * This argument is specified in Hz * A good value for this is 150 - remove_low_frequency_ * This argument specifies whether or not to remove low frequency noise. * Can be either HIGH_PASS_FILTER_ON (remove low frequency noise) or HIGH_PASS_FILTER_OFF * If the EMG signal does not pass through an analog high pass filter, it is highly recommended to enable this feature * Disabling this feature decreases latency slightly - reference_available_ * This specifies whether a reference signal will be provided (in which case filter_EMG_r will be called instead of filter_EMG) * Can be either REFERENCE_AVAILABLE or REFERENCE_UNAVAILABLE ------------------------------------------- ```c void free_EMG(EMG *self); ``` The destructor. Takes an EMG pointer as argument. ------------------------------------------- ```c int filter_EMG(EMG *self, int data); ``` This function is used to input the most recent data point and returns the most recent filtered EMG value. High and low frequency noise is removed from the signal. The signal is then rectified with respect to it's centre. A moving average filter returns the completely filtered EMG signal. The returned signal is indirectly proportional to the effort exerted by the muscle. This function must be called at the frequency specified in the constructor. - self * A A pointer to the EMG struct - data * The most recent raw data point ------------------------------------------- ```c int filter_EMG_r(EMG *self, int data, int reference_data); ``` This is the same as filter_EMG, except a reference data point must also be specified. This can only be called if REFERENCE_AVAILABLE was specified in the constructor. - reference_data * The most recent reference data point ------------------------------------------- ### 3) ECG PROCESSING (requires further development) - This library provides a tool to derive the BPM indicated by an ECG signal - The module uses the following steps to achieve this: * Initialization: 1. Find the average peak to peak values (the difference between the maximum and minimum values over a small peroid of a signal) of the signal over the first 3 seconds of operation 2. If the autodetect threshold feature is enabled, also find the average of the greatest peak to peak values over this time and calculate the threshold by dividing this value by the average value and multiplying by a hard-coded fraction (feel free to change this to tune the autodetect feature) * Normal operation: 1. When the latest peak to peak value of the signal surpasses the average found during initialization multiplied by the threshold, that instant is registered as a heart beat. 2. Heart now cannot be detected for 1/2 times the interval between the last two beats detected 3. Calculate the number of data points since the last heartbeat was detected and store the number 4. Take the average of the number of samples between the last 3 heartbeats. Use this value to calculate beats per minute (BPM) with the formula 60*sample_frequency/average_number_of_samples ------------------------------------------- ```c typedef enum { REFERENCE_AVAILABLE, REFERENCE_UNAVAILABLE, AUTODETECT_THRESHOLD_ON, AUTODETECT_THRESHOLD_OFF } ECG_OPTIONS; ``` An enum for the options that must be specified when creating a new ECG struct. ------------------------------------------- ```c ECG *new_ECG(uint16_t sample_frequency_, float pkpk_threshold_ratio_, ECG_OPTIONS reference_availability_, ECG_OPTIONS autodetect_); ``` This is the constructor for the ECG struct. It returns a pointer to the newly created struct. - sample_frequency_ * This is the constant frequency in which data will be given (the frequency which get_BPM or get_BPM_r will be called) - pkpk_threshold_ratio_ * This is the ratio of peak to peak voltage during ventricular depolarization and the PR interval. * This value differs slightly between each ECG setup and must be determined by experimentation. * Alternatively, you can use the autodetect_ feature, which allows the soft