Hybrid sEMG + IMU activated controller for Galileo Bionic Hand Prosthesis

Dependencies:   FXAS21000 FXOS8700Q kalman mbed-dsp mbed-rtos mbed

Files at this revision

API Documentation at this revision

Comitter:
julioefajardo
Date:
Sun Nov 01 18:38:43 2015 +0000
Parent:
0:2245e978868c
Commit message:
Version 1.5 - RTOS; Threads; Mutex; EMG sampler; IMU sampler; Kalman filter; Serial Communication; Feature Extraction; Neural Network Classifier

Changed in this revision

main.cpp Show annotated file Show diff for this revision Revisions of this file
rtwtypes.h Show annotated file Show diff for this revision Revisions of this file
diff -r 2245e978868c -r 84347af5a1f2 main.cpp
--- a/main.cpp	Fri Oct 16 21:29:22 2015 +0000
+++ b/main.cpp	Sun Nov 01 18:38:43 2015 +0000
@@ -4,6 +4,7 @@
 #include "rtos.h"
 #include "kalman.c"
 #include "arm_math.h" 
+#include "rtwtypes.h"
 
 #define TRUE            1
 #define FALSE           0
@@ -24,6 +25,7 @@
 FXOS8700Q_mag combo_mag(D14, D15, FXOS8700CQ_SLAVE_ADDR1);
 FXAS21000 gyro(D14, D15);
 DigitalOut led1(LED1);
+DigitalOut led2(LED2);
 InterruptIn sw2(SW2);
 Timer GlobalTime;
 Timer ProgramTimer;
@@ -42,24 +44,66 @@
 float32_t abs_output[25];
 float32_t abs_output2[25];
 float32_t abs_output3[25];
-float32_t mean = 0.0f;
-float32_t mean2 = 0.0f; 
-float32_t mean3 = 0.0f;
+float32_t MAV1 = 0.0f;
+float32_t MAV2 = 0.0f; 
+float32_t MAV3 = 0.0f;
+
+typedef struct {
+  float32_t iemg;
+    float32_t wl;
+  float32_t var;
+  int32_t wamp;
+  int32_t zc;
+  int32_t ssc;  
+} emg_features;
+
+emg_features feat1 = {0.0f,0.0f,0.0f,0,0,0};
+emg_features feat2 = {0.0f,0.0f,0.0f,0,0,0};
 
 //IMU
-float gyro_data[3];
+float32_t gyro_data[3];
 MotionSensorDataUnits adata;
 MotionSensorDataUnits mdata;
-float R;
-float angle[3];
-float roll;
-float pitch;
+float32_t R;
+float32_t R_XY;
+float32_t R_mean;
+float32_t angle[3];
+float32_t roll;
+float32_t pitch;
 kalman filter_pitch; 
 kalman filter_roll;
+kalman filter_yaw;
+float32_t imu_ones[25];
+float32_t accx_samples[25];
+float32_t accy_samples[25];
+float32_t accz_samples[25];
+float32_t roll_samples[25];
+float32_t pitch_samples[25];
+float32_t R_samples[25];
+float32_t imu_abs_samples[25];
+
+
+typedef struct {
+  float32_t l1;
+  float32_t mean;
+  float32_t var;
+} imu_features;
+
+imu_features ax_feat = {0.0f,0.0f,0.0f};
+imu_features ay_feat = {0.0f,0.0f,0.0f};
+imu_features az_feat = {0.0f,0.0f,0.0f};
+imu_features pitch_feat = {0.0f,0.0f,0.0f};
+imu_features roll_feat = {0.0f,0.0f,0.0f};
+imu_features R_feat = {0.0f,0.0f,0.0f};
+
+float32_t imu_y[4] = {0.0f,0.0f,0.0f,0.0f};                                                                                                                                             //neural network output
+float32_t imu_x[18] = {0.0f,0.0f,0.0f,0.0f,0.0f,0.0f,0.0f,0.0f,0.0f,0.0f,0.0f,0.0f,0.0f,0.0f,0.0f,0.0f,0.0f,0.0f};              //imu neural network input
+float32_t imu_max = 0.0f;                                                                                                   //max accuracy
+uint32_t imu_class = 0;                                                                                                     //class
 
 //OS    
-osMutexId el_mutex;
-osMutexDef(el_mutex);                                          
+Mutex imu_mutex;
+Mutex emg_mutex;                                          
  
 //time 
 unsigned long timer;
@@ -69,24 +113,31 @@
 void button_thread(void const *argument);
 void imu_thread(void const *argument);
 void sampler_thread(void const *argument);
-void logger_thread(void const *argument);
+void imu_proc_thread(void const *argument);
 
+imu_features imuGetFeatures(float32_t samples[50]);
 void Serial_Oscilloscope(uint8_t activation, uint8_t type);
+void IMU_Logger(void);
+void IMU_Classifier(const float x1[18], float b_y1[4]);
+boolean_T rtIsNaNF(real32_T value);
 
 int main(void)
 {
     pc.baud(115200);                                  //Serial com at 115200 bauds
+    led1 = 1; led2 = 1;
     Thread thread(imu_thread);
     thread2 = new Thread(button_thread);
     thread3 = new Thread(sampler_thread);
-    thread4 = new Thread(logger_thread);
-    el_mutex = osMutexCreate(osMutex(el_mutex));
+    thread4 = new Thread(imu_proc_thread);
+    
+    arm_fill_f32(1.0f, imu_ones, 50);
+    
     GlobalTime.start();
     
     combo_acc.enable();
     combo_mag.enable();
-    pc.printf("FXOS8700 Combo = %X\r\n", combo_acc.whoAmI());
-    pc.printf("FXAS21000 Gyro = %X\r\n", gyro.getWhoAmI());
+    //pc.printf("FXOS8700 Combo = %X\r\n", combo_acc.whoAmI());
+    //pc.printf("FXAS21000 Gyro = %X\r\n", gyro.getWhoAmI());
     
     kalman_init(&filter_pitch, R_matrix, Q_Gyro_matrix, Q_Accel_matrix); 
     kalman_init(&filter_roll, R_matrix, Q_Gyro_matrix, Q_Accel_matrix);
@@ -99,12 +150,15 @@
     timer = loopStartTime;
     
     while (true) {
-        Thread::wait(5000);
         led1 = !led1;
-        pc.printf("SW2 was pressed (last 5 seconds): %d \n\r", button_pressed);
-        pc.printf("Roll Angle X: %.6f   Pitch Angle Y: %.6f \r\n", Rad2Dree * angle[1], Rad2Dree * angle[0]);
-        fflush(stdout);
+        //pc.printf("SW2 was pressed (last 5 seconds): %d \n\r", button_pressed);
+        //pc.printf("Acc Vector: %.6f   XY Acc Vector: %.6f  Roll Angle X: %.6f   Pitch Angle Y: %.6f \r\n", R, R_XY, Rad2Dree * angle[1], Rad2Dree * angle[0]);
+        //fflush(stdout);
+        //pc.printf("%.6f,%.6f,%.6f,%.6f,%.6f,%.6f\r",adata.x,adata.y,adata.z,R_XY,angle[0],angle[1]);
+        
         button_pressed = 0;
+        Thread::wait(100);
+        
     }
 }
 
@@ -122,10 +176,11 @@
 void imu_thread(void const *argument){
     while (true) {
         
-        combo_acc.getAxis(adata); //pc.printf("FXOS8700 Acc:   X:%6.3f Y:%6.3f Z:%6.3f\r\n", adata.x, adata.y, adata.z);
-        combo_mag.getAxis(mdata); //pc.printf("FXOS8700 Mag:   X:%6.2f Y:%6.2f Z:%6.2f\r\n", mdata.x, mdata.y, mdata.z);
-        gyro.ReadXYZ(gyro_data);  //pc.printf("FXAS21000 Gyro: X:%6.2f Y:%6.2f Z:%6.2f\r\n", gyro_data[0], gyro_data[1], gyro_data[2]);
+        combo_acc.getAxis(adata); 
+        gyro.ReadXYZ(gyro_data);  
+        
         R = sqrt(std::pow(adata.x, 2) + std::pow(adata.y, 2) + std::pow(adata.z, 2));
+        R_XY = sqrt(std::pow(adata.x, 2) + std::pow(adata.y, 2));
         
         kalman_predict(&filter_pitch, gyro_data[0],  (ProgramTimer.read_us() - timer)); 
         kalman_update(&filter_pitch, acos(adata.x/R));
@@ -134,6 +189,25 @@
         
         angle[0] = kalman_get_angle(&filter_pitch);
         angle[1] = kalman_get_angle(&filter_roll);
+        
+        imu_mutex.lock();
+        for(int j=25-1;j>0;j--) {
+            accx_samples[j]=accx_samples[j-1];                  
+            accy_samples[j]=accy_samples[j-1];                  
+            accz_samples[j]=accz_samples[j-1];                
+            roll_samples[j]=roll_samples[j-1];
+            pitch_samples[j]=pitch_samples[j-1];
+            R_samples[j]=R_samples[j-1];
+        }
+        accx_samples[0]=adata.x;
+        accy_samples[0]=adata.y;
+        accz_samples[0]=adata.z;
+        roll_samples[0]=angle[1];
+        pitch_samples[0]=angle[0];
+        R_samples[0]=R_XY;
+        imu_mutex.unlock();
+        
+        thread4->signal_set(0x1);
         Thread::wait(10);
     }
 }
@@ -143,7 +217,6 @@
         EMG1 = (E1.read()-Ref.read())*3.3f;
         EMG2 = (E2.read()-Ref.read())*3.3f;
         EMG3 = (E3.read()-Ref.read())*3.3f;
-        //osMutexWait(el_mutex, osWaitForever);        
         for(int j=24;j>0;j--) {
             samples[j]=samples[j-1];                    //Fill Array
             samples2[j]=samples2[j-1];                  //Fill Array
@@ -152,15 +225,56 @@
         samples[0]=EMG1;
         samples2[0]=EMG2;
         samples3[0]=EMG3;       
-        //osMutexRelease(el_mutex);
         Thread::wait(1);
     }
 }
 
 
-void logger_thread(void const *argument){
+void imu_proc_thread(void const *argument){
     while (true) {
-        Thread::wait(50);
+        //int i;
+        Thread::signal_wait(0x1);
+        imu_mutex.lock();
+        arm_mean_f32(R_samples, 25, &R_mean);
+        if(R_mean>=1.125f){
+            //for(i=0;i<25;i++) pc.printf("%.6f,",accx_samples[i]);
+            ax_feat = imuGetFeatures(accx_samples);
+            ay_feat = imuGetFeatures(accy_samples);
+            az_feat = imuGetFeatures(accz_samples);
+            R_feat = imuGetFeatures(R_samples);
+            pitch_feat = imuGetFeatures(pitch_samples);
+            roll_feat = imuGetFeatures(roll_samples);
+            //IMU_Logger();
+            imu_x[0] = ax_feat.l1; 
+            imu_x[1] = ax_feat.mean; 
+            imu_x[2] = ax_feat.var;
+            imu_x[3] = ay_feat.l1; 
+            imu_x[4] = ay_feat.mean; 
+            imu_x[5] = ay_feat.var;
+            imu_x[6] = az_feat.l1; 
+            imu_x[7] = az_feat.mean; 
+            imu_x[8] = az_feat.var;
+            imu_x[9] = R_feat.l1; 
+            imu_x[10] = R_feat.mean;
+            imu_x[11] = R_feat.var;
+            imu_x[12] = pitch_feat.l1;
+            imu_x[13] = pitch_feat.mean; 
+            imu_x[14] = pitch_feat.var; 
+            imu_x[15] = roll_feat.l1;
+            imu_x[16] = roll_feat.mean;
+            imu_x[17] = roll_feat.var;
+            IMU_Classifier(imu_x,imu_y);
+            arm_max_f32(imu_y,4,&imu_max,&imu_class);
+            pc.printf("%d ",imu_class);
+            switch(imu_class){
+                case 0: pc.printf("Up\n\r"); break;
+                case 1: pc.printf("Down\n\r"); break;
+                case 2: pc.printf("Left\n\r"); break;
+                case 3: pc.printf("Right\n\r"); break;
+            }       
+        }
+        imu_mutex.unlock();
+        Thread::wait(500);
     }
 }
 
@@ -169,8 +283,403 @@
         switch(type){
             case RAW: pc.printf("%.10f,%.10f,%.10f\n\r",EMG1,EMG2,EMG3); break; 
             case RECTIFIED: pc.printf("%.10f,%.10f,%.10f\n\r",abs_output[0],abs_output2[0],abs_output3[0]);break;
-            case SMOOTH: pc.printf("%.10f,%.10f,%.10f\n\r",mean,mean2,mean3); break;
+            case SMOOTH: pc.printf("%.10f,%.10f,%.10f\n\r",MAV1,MAV2,MAV3); break;
             default: pc.printf("%.10f,%.10f,%.10f\n\r",EMG1,EMG2,EMG3); 
         } 
     }    
 }
+
+void IMU_Logger(void){
+    pc.printf("%.10f,%.10f,%.10f,%.10f,%.10f,%.10f,%.10f,%.10f,%.10f\r",ax_feat.l1,ax_feat.mean,ax_feat.var,ay_feat.l1,ay_feat.mean,ay_feat.var,az_feat.l1,az_feat.mean,az_feat.var);
+    pc.printf("%.10f,%.10f,%.10f,%.10f,%.10f,%.10f,%.10f,%.10f,%.10f\r",R_feat.l1,R_feat.mean,R_feat.var,pitch_feat.l1,pitch_feat.mean,pitch_feat.var,roll_feat.l1,roll_feat.mean,roll_feat.var);
+}
+
+imu_features imuGetFeatures(float32_t samples[25]){
+    imu_features feat;
+    float32_t l1, mean, var;
+            
+    /*L1*/
+    arm_abs_f32(samples, imu_abs_samples, 25);   
+    arm_dot_prod_f32(imu_abs_samples, imu_ones, 25, &l1);
+    
+    /*MAV*/
+    arm_mean_f32(imu_abs_samples, 25, &mean);
+    /*variance*/
+    arm_var_f32(samples, 25, &var);
+    
+    feat.l1 = l1;
+    feat.mean = mean;
+    feat.var = var;
+    
+    return feat;
+}
+
+void IMU_Classifier(const float x1[18], float b_y1[4]){
+  float xp1[18];
+  int ixstart;
+  static const double settings_gain[18] = { 0.0615861197203374, 1.53965323006161,
+    0.857469392512132, 0.0600806679095755, 1.50201694590539, 1.23879030268757,
+    0.0663679885953248, 1.65919957723595, 0.599294154820359, 0.113465456292823,
+    2.83663399337079, 2.21904272848878, 0.053290743371231, 1.33226929425699,
+    2.74309649260372, 0.0572933421985231, 1.43233365754206, 2.73777852926756 };
+
+  static const double settings_xoffset[18] = { 3.13208, 0.1252832, 0.01800423,
+    9.610352, 0.3844141, 0.06231475, 16.18701, 0.6474805, 0.008212686, 28.19626,
+    1.12785, 0.06004226, 23.18947, 0.927579, 0.006299257, 12.31171, 0.4924683,
+    0.02629572 };
+
+  double b[45];
+  static const double a[45] = { -1.7580289769551161, -1.3423592326953466,
+    1.5454917034757418, 1.6192469035519192, 1.1088397665812808,
+    -1.3294886162934598, -1.5402696585790496, -1.0670236222833622,
+    0.79657239712499928, -0.67248449362717955, -0.93265917892314076,
+    0.51780467293444077, 0.75531292620200852, 0.68952452013799781,
+    -0.9167788050264305, 0.40679456848166357, -0.78466204076547852,
+    0.0746048711915274, -0.352749928885278, 0.017737649172833974,
+    -0.038510072629115363, -0.20772701105519994, 0.45325062847723907,
+    0.26044952985819775, 0.39677487553689345, -0.078712365946250917,
+    -0.0825777988627018, -0.4727716865854944, 0.527910227195504,
+    -0.74851602503119774, 0.63024557363169653, -0.58582825900364521,
+    0.68849439469421991, -0.84750206038432641, -1.2000641131247758,
+    -0.832240518854391, 1.0889450399496252, -1.3059529805809877,
+    -1.4651416897453897, 1.3742855905702005, 1.2927860034088354,
+    1.60109353014912, 1.4478939752003774, -1.6843870868642861,
+    1.8617437390920597 };
+
+  float b_b[45];
+  int ix;
+  float denom;
+  static const float fv0[810] = { 0.459632903F, 0.0611374F, -0.421426982F,
+    0.148853645F, -0.177980483F, 0.247128889F, 0.214431226F, 0.451934367F,
+    -0.532601058F, 0.0238353293F, 0.497370124F, -0.575586F, -0.499140948F,
+    -0.0641773343F, 0.53166759F, 0.0778795481F, 0.225708947F, -0.498524398F,
+    0.694334269F, -0.60842818F, 0.325595617F, 0.252601981F, 0.365996331F,
+    0.384501338F, 0.00875493512F, -0.4245179F, -0.668958485F, -0.683882117F,
+    0.181472883F, -0.426831633F, 0.297112852F, -0.583310187F, 0.456262171F,
+    -0.459338129F, -0.641833425F, -0.459789753F, 0.204319239F, -0.186706707F,
+    -0.285366446F, 0.640228748F, 0.0229709782F, -0.0642111823F, 0.553962111F,
+    -0.33109349F, 0.247776791F, 0.443146557F, -0.542193532F, 0.119367629F,
+    -0.451677382F, -0.786408F, 0.0928186F, 0.316778958F, 0.707230628F,
+    -0.746820033F, -0.147853762F, 0.219747201F, -0.79193157F, -0.194468275F,
+    -0.499102324F, 0.274141163F, 0.022611469F, 0.128222346F, -0.607686698F,
+    0.48310256F, -0.593217313F, 0.536703944F, 0.2398123F, 0.150423944F,
+    -0.336881399F, -0.769578874F, -0.308003962F, 0.29553327F, -0.83044821F,
+    0.161142096F, -0.0343337208F, 0.581449211F, -0.873495698F, -0.28423211F,
+    -0.78573F, 0.383646518F, -0.753481686F, 0.452582896F, 0.226794824F,
+    0.375832409F, -0.498845309F, -0.258810967F, -0.499766558F, 0.404769868F,
+    -0.0505502634F, 0.461976469F, -0.389700621F, -0.713240385F, -0.481977165F,
+    -0.441101372F, 0.769881368F, 0.228649467F, 0.113842353F, -0.513090611F,
+    0.57655704F, 0.00201666565F, -0.0780342743F, -0.0782211572F, -0.263174862F,
+    -0.454693228F, -0.401941508F, -0.28711313F, -0.51956F, -0.413541466F,
+    -0.0222236887F, -0.825855196F, 0.663189113F, 0.648147404F, -0.120558769F,
+    -0.216713682F, -0.42545253F, 0.63155061F, -0.410026342F, -0.737376034F,
+    0.199930415F, -0.214675143F, -0.65693754F, -0.323603958F, -0.831128061F,
+    -0.548523843F, 0.398182899F, 0.475979269F, -0.111701392F, -0.558011353F,
+    -0.246838376F, -0.176599175F, 0.494953543F, -0.930735171F, -0.485517114F,
+    -0.660200715F, -0.151493624F, 0.239350051F, 0.50181222F, -0.0828042775F,
+    -0.0873984F, -0.215416417F, 0.192907035F, -0.3374F, 0.213343263F,
+    -0.400835454F, -0.206182152F, -0.0448735021F, 0.67194277F, -0.42755118F,
+    1.01745749F, 0.661765158F, -0.494972438F, 0.0940658301F, 0.00391307333F,
+    -0.407710791F, 0.106923632F, -0.206497744F, 0.754692852F, 0.176430732F,
+    0.385327101F, 0.0846962854F, 0.323739618F, -0.151615232F, 0.174422458F,
+    0.740742445F, 0.591877937F, 0.223434791F, 0.334855318F, 0.282185555F,
+    -0.214522555F, -0.0105024902F, 0.273585677F, 0.114028879F, 0.543323517F,
+    -0.291319072F, -0.432583898F, -0.821406F, -0.251906455F, -0.0459434502F,
+    -0.455817074F, 0.483560562F, -0.182349116F, -0.171598256F, 0.561632752F,
+    0.540451586F, 0.0060411403F, -0.653444648F, -0.236067981F, -0.182513028F,
+    0.202278212F, -0.370738387F, -0.0789217F, 0.572875738F, -0.231134444F,
+    -0.0330054797F, -0.0838245675F, -0.813296914F, 0.0739755705F, 0.118539378F,
+    -0.72018075F, -0.368218392F, 0.207165778F, -0.267799765F, 0.378820896F,
+    0.507289112F, 0.269455492F, 0.0232036524F, -0.524693549F, 0.325159252F,
+    0.773608327F, 0.137095451F, 0.178058892F, -0.351133883F, 0.132823557F,
+    0.34390527F, 0.495856106F, 0.183722347F, 0.328040898F, 0.716017127F,
+    -0.492127508F, 0.573495567F, 0.306710184F, 0.602395654F, -0.475191712F,
+    -0.550692558F, -0.337273896F, 0.232871071F, -0.414121956F, 0.338607788F,
+    -0.689573646F, 0.449012369F, 0.100024827F, 0.379222423F, 0.189025134F,
+    0.843987286F, 0.693846166F, -0.185747191F, 0.0946606621F, -0.453255206F,
+    -1.33637404F, 0.19069238F, 0.126079515F, -0.0326298513F, 0.788161218F,
+    0.135455295F, 0.336440802F, 0.425412089F, 0.102825224F, 0.63407582F,
+    -0.270895481F, -0.720058799F, 0.695959747F, -0.023164358F, -0.0242635924F,
+    -0.671196F, 0.554490209F, 0.190925688F, 0.272486627F, -0.0107945595F,
+    -0.742727757F, 0.13697502F, -0.775040329F, -0.71145767F, 0.26798436F,
+    -0.377285868F, 0.252919018F, 1.06671643F, -0.13240622F, -0.494904369F,
+    0.453439087F, 0.132181391F, 0.668464959F, 0.501227736F, 0.424547732F,
+    -0.280139863F, -0.019443851F, 0.542961895F, -0.512611568F, -0.559954345F,
+    -0.339779437F, 0.0962056518F, 0.247770652F, 0.970269084F, -0.098800607F,
+    0.0772119F, 0.165748924F, -0.425046772F, 0.372346252F, 0.561903596F,
+    -0.465825468F, -0.00290585565F, -0.882256508F, 1.38634479F, -0.292974889F,
+    -0.342612416F, 0.0741659775F, -0.297257066F, 0.423533231F, 0.0936212242F,
+    0.603145778F, 0.517324328F, -0.739661038F, 0.644301593F, -0.291442573F,
+    0.0685671866F, 0.0421827547F, 0.463616759F, 0.574609816F, 0.732411F,
+    -0.103880793F, 0.14776741F, 0.350388736F, 0.034289483F, 0.228362814F,
+    0.623231232F, -0.854294896F, -0.513297081F, 1.01049197F, -0.468677133F,
+    -0.89124316F, 0.180666521F, 0.618507206F, 0.34617874F, -0.478432477F,
+    -0.0531243756F, 0.204267785F, 0.472398907F, 0.0415514335F, 1.01171207F,
+    0.394830078F, -0.0686556473F, -0.852999389F, -0.0204684064F, 0.2879785F,
+    -0.70830971F, 0.301956505F, -0.581959546F, 0.608920038F, 0.334958166F,
+    -0.136173159F, -0.063511923F, 0.243027285F, 0.140252739F, 0.769615531F,
+    0.645489156F, 0.254678458F, -0.284347504F, 0.374404907F, -0.536988378F,
+    0.717072845F, 0.486760736F, 0.31468308F, 0.329237908F, 0.265202075F,
+    -0.460599929F, -0.273192674F, -0.18682602F, -0.533184588F, -0.433163792F,
+    0.153697655F, -0.971417725F, 0.0716149211F, 0.388068318F, 0.304798931F,
+    0.0493364856F, 0.525654316F, -0.734183729F, -0.418183059F, -0.391056359F,
+    0.349859178F, 0.295310169F, -0.162787989F, 0.986191332F, 0.893915057F,
+    0.468418807F, 0.227301195F, -0.893956F, -0.0392929763F, 0.547721744F,
+    0.277446F, 0.0684096217F, -0.817378163F, 0.294014931F, -0.789526939F,
+    -0.101080045F, 0.1247008F, 0.390003234F, 0.123767406F, 0.819431722F,
+    -0.075544F, 0.692092419F, -0.023473734F, 1.12595487F, -0.0727373213F,
+    0.185063079F, -0.127668485F, 0.0907674953F, 1.01107F, 0.103436872F,
+    -0.104357071F, -0.612592816F, 0.118782118F, 0.294045866F, -0.182440594F,
+    0.632002592F, 0.443847477F, -0.648681045F, 0.0449045971F, -0.132676274F,
+    0.650167644F, -0.520409822F, -0.00697870459F, -0.0560558848F, -0.0724578276F,
+    0.488136113F, -0.304092556F, 0.362224847F, 0.15520215F, -0.527926445F,
+    -0.353179634F, 0.369286567F, -0.05207555F, -0.510196149F, -0.129422769F,
+    0.190302268F, -0.544416964F, 0.247901723F, -0.173602447F, 0.65681529F,
+    -0.372931182F, 0.239432991F, -0.3728562F, -0.289556086F, -0.465267807F,
+    -0.0267323405F, 0.211196959F, -0.0809709206F, -0.211201906F, 0.0164073836F,
+    0.211801484F, 0.28273347F, 0.24367331F, 0.712016702F, -0.232072771F,
+    0.352156729F, -0.413937926F, -0.67757833F, -0.0740010217F, 0.0034886F,
+    0.10386055F, 0.491702259F, 0.419249F, -0.321603328F, 0.258051783F,
+    -0.0750256628F, 0.785783052F, 0.487906694F, -0.302251101F, 0.144713297F,
+    0.212649152F, 0.0338810794F, 0.489597201F, -0.141343772F, -0.133599311F,
+    -0.426484972F, 0.708699524F, 0.27392745F, 0.05124259F, 0.430232316F,
+    0.101622045F, 0.335402131F, -0.0293640438F, 0.446573496F, 0.0604294352F,
+    0.654577732F, -0.67903477F, -0.479712456F, -0.514000893F, -0.50363785F,
+    -0.260914654F, -0.113499187F, -0.363629967F, 0.381589234F, -0.00877389684F,
+    0.378615469F, 0.622865498F, 0.64521867F, -0.464941829F, -0.316285223F,
+    0.33551228F, -0.631272078F, -0.0607743897F, -0.189647585F, 0.527016699F,
+    0.154212683F, 0.116914578F, 0.183713183F, 0.346713036F, 0.0502914973F,
+    -0.170981154F, -0.47873193F, -0.103974499F, -0.296331912F, -0.682696223F,
+    0.418706745F, -0.702610731F, 0.113047369F, 0.11163982F, -0.219719663F,
+    -0.265369058F, -0.304860383F, 0.247510567F, 0.605953753F, -0.221037015F,
+    -0.479578376F, -0.364096701F, 0.232404232F, -0.923531771F, -0.607895613F,
+    0.379731268F, -0.63160032F, 0.704049F, -0.623289347F, 0.211085469F,
+    -0.201172546F, 0.496017128F, 0.111459091F, -0.216925532F, -0.456628412F,
+    0.264619768F, 0.478987068F, -0.304841787F, 0.143561065F, 0.12293458F,
+    0.41051206F, 0.242302909F, -0.755550683F, 0.268951803F, 0.669802606F,
+    -0.444868356F, 1.0796355F, 0.0833751F, -0.494852066F, -0.434321523F,
+    -0.0662497878F, 0.282435954F, 0.518994629F, 0.440311342F, -0.314596683F,
+    -0.00901326071F, -0.16180931F, -0.645285F, -0.405436337F, 0.182191074F,
+    0.295300335F, -0.322578758F, 0.196225166F, -0.502243817F, -0.786416531F,
+    0.523073316F, 0.118213534F, 0.408718884F, -0.063704811F, 0.104132973F,
+    0.582743F, 0.927500665F, 0.20945847F, -0.929123461F, 0.632320702F,
+    0.172647551F, 0.653148234F, -0.099445492F, -0.0184663199F, 0.563922763F,
+    -0.247307703F, 0.08971598F, 0.270614028F, 0.235931277F, 0.593309343F,
+    0.293943584F, 0.189385429F, -0.65996927F, -0.21901688F, -0.583070755F,
+    0.341855168F, 1.1340152F, 0.281593F, 0.575785697F, 0.676429689F, 0.459074F,
+    0.0225899909F, 0.656224668F, 0.132585585F, -0.743888676F, -0.614794552F,
+    1.03475749F, -0.0882811099F, 0.611714F, -0.473244578F, 0.369189858F,
+    0.362521559F, -0.681019485F, 0.300381541F, -0.209409952F, -0.610560894F,
+    -0.0188860334F, -0.641817153F, -0.807590604F, -0.465627879F, -0.365699679F,
+    -0.231352642F, -1.01078808F, -0.127937913F, -0.181259409F, 0.0717183352F,
+    0.24582836F, -0.144107684F, 0.0802998692F, 0.0219049808F, -0.386688113F,
+    0.0793484673F, 0.213585958F, 0.703600287F, -0.0976952165F, -0.3840639F,
+    0.157325551F, -0.0620508F, -0.593766451F, -0.427041501F, 0.962344646F,
+    0.325952917F, -0.481346279F, -0.883274317F, -0.448941231F, 0.281245708F,
+    0.416657F, -0.52693814F, 0.689424396F, 0.296314508F, 0.432173222F,
+    -0.828454316F, 0.726714194F, 0.523919344F, 0.516204655F, 0.442432255F,
+    0.45585233F, 0.376238436F, -0.461082667F, -0.151951969F, -0.449687511F,
+    -0.836503446F, 0.659184694F, -0.29375577F, -0.535523951F, -0.468601644F,
+    -0.293337F, 0.365438163F, -0.737874627F, 0.190893024F, -0.0833086F,
+    0.492872238F, -0.434281528F, -0.282535583F, -0.805321336F, -0.503223121F,
+    0.0819781274F, -0.249333F, -0.0285112094F, -0.352597207F, 0.724770725F,
+    0.15054968F, 0.319918931F, 0.62603879F, -0.160482243F, -0.16062668F,
+    -0.27161333F, 0.346072078F, 0.537718773F, -0.552904546F, -0.494646609F,
+    -0.336943179F, -0.669887364F, -0.00652140286F, -0.222761601F, -0.604594052F,
+    -0.723421872F, 0.733910799F, 0.463824034F, 0.26406005F, 0.419488341F,
+    -0.69037348F, 0.441993326F, 0.737772286F, 0.243240789F, -0.262164325F,
+    0.143315554F, -0.142399684F, -0.079456754F, -0.746082723F, 0.56054467F,
+    -0.576788604F, -0.162682116F, -0.661055088F, -0.0100884913F, -0.84846276F,
+    0.502910495F, -0.556128383F, -0.381545156F, -0.226393521F, -0.290395468F,
+    -0.638160288F, 0.405303419F, 0.45708254F, -0.231018662F, -0.600171506F,
+    -0.317634284F, -0.796222687F, -0.0962729752F, 0.302519232F, 0.227096081F,
+    -0.697582F, -0.609304726F, 0.478130311F, 0.589749038F, 0.0213635098F,
+    -0.726078153F, 0.357511342F, -0.27600044F, -0.282378614F, 0.232002884F,
+    -1.03095603F, -0.546820879F, 0.453093469F, 0.452624887F, -0.0799274892F,
+    0.28348428F, 0.36944288F, 0.815283835F, -0.270792842F, 0.45711121F,
+    0.0650191829F, -0.00474550668F, -0.173524231F, 0.111019306F, -0.22976172F,
+    0.324191928F, 0.480501801F, -0.596600354F, -0.44761616F, -0.116759337F,
+    -0.0663144886F, 0.528708041F, 0.85675323F, 0.423383653F, -0.833274245F,
+    -0.676730037F, -0.675398231F, 1.18571389F, 0.545059323F, 0.194837719F,
+    -0.571213663F, 0.231315166F, -0.689943135F, -0.517713F, 0.245689139F,
+    -0.36406526F, 0.159462124F, 0.377790302F, 0.15022406F, 0.203641087F,
+    -0.231097415F, 0.311318755F, 0.771822393F, 0.402989596F, -0.383682787F,
+    -0.434375495F, -0.156969324F, 0.271495759F, 0.100708269F, 0.0158944763F,
+    -0.182064518F, -0.46497798F, -0.53833F, 0.636102617F, -0.416234672F,
+    -0.0785247087F, -0.0448715724F, -0.431249201F, 0.146780565F, 0.031037325F,
+    -0.75488F, 0.38843447F, -0.295456231F, -0.127952173F, -0.481856853F,
+    0.130730167F, -0.694406748F, 0.0459047593F, -0.53592F, -0.676697969F,
+    0.458953559F, -0.456679523F, 0.348396122F, 0.657496393F, 0.0483298F,
+    0.143341869F, 0.715741456F, -0.366335869F, 0.218585283F, -0.794284F,
+    0.618138731F };
+
+  float x[45];
+  double c_b[4];
+  static const double b_a[4] = { 0.843573525672487, 0.52887395783527291,
+    0.67012100803296748, 0.49760939396991682 };
+
+  float numer[4];
+  static const float fv1[180] = { -0.576368749F, -0.461289287F, 0.359091967F,
+    0.156713441F, 1.09660339F, -0.57649368F, -0.868483543F, -0.701349378F,
+    0.437389016F, -0.0926702321F, 0.103165969F, -0.118973181F, -0.839078665F,
+    -0.364395678F, 0.698953509F, 0.193260536F, -0.757779062F, -0.571485519F,
+    -0.66037178F, -1.29905105F, -0.201243833F, 0.485816419F, 0.798221F,
+    -0.417164803F, -0.831456721F, 0.145439208F, -0.624888301F, -0.686319172F,
+    -1.01671267F, -0.952691317F, -0.346321493F, -0.474031448F, -0.466582507F,
+    -0.434489608F, 0.0789648071F, -0.972864866F, 0.628803194F, 0.82423836F,
+    0.392369598F, -1.1727767F, -0.51170367F, -0.79655838F, 0.487405777F,
+    0.640642822F, 1.03092039F, -0.718461812F, -0.919755638F, -0.072865434F,
+    1.09984982F, -0.727400839F, -0.270503879F, -0.476028502F, -0.577538967F,
+    0.310665369F, -0.786185086F, 1.33968735F, -0.261592031F, 0.159126773F,
+    -0.615301311F, -0.165091559F, -0.919524F, 0.589730442F, 0.887396574F,
+    -0.275334418F, 0.369588107F, -0.644339323F, 0.131432697F, 0.828792572F,
+    0.634907126F, -0.218690842F, -0.779631317F, -0.26734677F, -0.51404953F,
+    -0.538019836F, 0.493474483F, 0.724827945F, -0.0821629688F, 0.126185417F,
+    -0.86919862F, -1.1688292F, -0.788445175F, -0.743515372F, 1.08614969F,
+    0.882474661F, 0.943030596F, 0.0328377932F, -0.917530715F, 0.737649441F,
+    0.37147674F, 0.572349489F, 0.534060121F, -0.778717935F, 0.111810587F,
+    -0.219216034F, -0.667796552F, -0.313792109F, 0.438846558F, -0.316282123F,
+    -1.13036656F, 0.664084792F, 1.1458832F, -0.0636171848F, 0.464452535F,
+    -1.01223803F, 0.634164453F, 0.317785263F, 0.492384404F, -1.02305794F,
+    1.06032813F, 0.77377373F, -1.05769241F, -0.370299608F, -0.465102851F,
+    0.62622422F, -0.640314877F, -0.148292065F, -0.208885193F, -0.709490895F,
+    -1.15019488F, 0.829242766F, 0.120800421F, 0.694289267F, -0.382296205F,
+    0.90905267F, 1.55740833F, -0.13578631F, -0.692770541F, -0.589448631F,
+    0.397961974F, -0.523246586F, -0.814948142F, 0.564497709F, 0.0221325234F,
+    1.3606391F, -0.130946055F, -0.356777936F, -0.273988575F, 0.733114958F,
+    -0.371666F, 0.590279281F, 1.07341897F, 0.694256663F, -0.389202297F,
+    0.186797455F, 1.00938177F, -0.705201328F, -0.808631361F, 1.14770544F,
+    0.814412832F, -0.400106907F, 0.402769178F, -0.402200758F, 0.122468233F,
+    0.0504386574F, -0.452429116F, -0.146729171F, -0.967114568F, -0.130777434F,
+    -0.37407282F, 0.184210435F, -0.377413243F, 0.806694806F, 1.11887777F,
+    -0.513802588F, -0.530572236F, 0.836555302F, -0.410351485F, 0.752652407F,
+    -0.644252837F, -0.311244279F, -0.628207624F, 0.233606949F, -0.431879401F,
+    -0.998878F, 0.732248843F, -0.708933234F, 0.0570094101F, -0.292068034F,
+    1.09782875F, -1.47580659F };
+
+  boolean_T exitg1;
+  float fv2[1];
+  boolean_T b_x;
+
+  /* MYNEURALNETWORKFUNCTION neural network simulation function. */
+  /*  */
+  /*  Generated by Neural Network Toolbox function genFunction, 30-Oct-2015 21:46:01. */
+  /*   */
+  /*  [y1] = myNeuralNetworkFunction(x1) takes these arguments: */
+  /*    x = 18xQ matrix, input #1 */
+  /*  and returns: */
+  /*    y = 4xQ matrix, output #1 */
+  /*  where Q is the number of samples. */
+  /*  ===== NEURAL NETWORK CONSTANTS ===== */
+  /*  Input 1 */
+  /*  Layer 1 */
+  /*  Layer 2 */
+  /*  ===== SIMULATION ======== */
+  /*  Dimensions */
+  /*  samples */
+  /*  Input 1 */
+  /*  ===== MODULE FUNCTIONS ======== */
+  /*  Map Minimum and Maximum Input Processing Function */
+  for (ixstart = 0; ixstart < 18; ixstart++) {
+    xp1[ixstart] = (x1[ixstart] - (float)settings_xoffset[ixstart]) * (float)
+      settings_gain[ixstart] + -1.0F;
+  }
+
+  /*  Layer 1 */
+  memcpy(&b[0], &a[0], 45U * sizeof(double));
+
+  /*  Sigmoid Symmetric Transfer Function */
+  for (ix = 0; ix < 45; ix++) {
+    denom = 0.0F;
+    for (ixstart = 0; ixstart < 18; ixstart++) {
+      denom += fv0[ix + 45 * ixstart] * xp1[ixstart];
+    }
+
+    b_b[ix] = (float)b[ix] + denom;
+  }
+
+  for (ix = 0; ix < 45; ix++) {
+    x[ix] = (real32_T)exp(-2.0F * b_b[ix]);
+  }
+
+  /*  Layer 2 */
+  for (ixstart = 0; ixstart < 4; ixstart++) {
+    c_b[ixstart] = b_a[ixstart];
+  }
+
+  for (ix = 0; ix < 45; ix++) {
+    b_b[ix] = 2.0F / (1.0F + x[ix]) - 1.0F;
+  }
+
+  for (ix = 0; ix < 4; ix++) {
+    denom = 0.0F;
+    for (ixstart = 0; ixstart < 45; ixstart++) {
+      denom += fv1[ix + (ixstart << 2)] * b_b[ixstart];
+    }
+
+    numer[ix] = (float)c_b[ix] + denom;
+  }
+
+  /*  Competitive Soft Transfer Function */
+  ixstart = 1;
+  denom = numer[0];
+  if (rtIsNaNF(numer[0])) {
+    ix = 2;
+    exitg1 = false;
+    while ((!exitg1) && (ix < 5)) {
+      ixstart = ix;
+      if (!rtIsNaNF(numer[ix - 1])) {
+        denom = numer[ix - 1];
+        exitg1 = true;
+      } else {
+        ix++;
+      }
+    }
+  }
+
+  if (ixstart < 4) {
+    while (ixstart + 1 < 5) {
+      if (numer[ixstart] > denom) {
+        denom = numer[ixstart];
+      }
+
+      ixstart++;
+    }
+  }
+
+  for (ixstart = 0; ixstart < 4; ixstart++) {
+    numer[ixstart] = (real32_T)exp(numer[ixstart] - denom);
+  }
+
+  denom = numer[0];
+  for (ixstart = 0; ixstart < 3; ixstart++) {
+    denom += numer[ixstart + 1];
+  }
+
+  fv2[0] = denom;
+  b_x = (denom == 0.0F);
+  ixstart = 0;
+  if (b_x) {
+    ixstart = 1;
+  }
+
+  ix = 0;
+  while (ix <= ixstart - 1) {
+    fv2[0] = 1.0F;
+    ix = 1;
+  }
+
+  for (ixstart = 0; ixstart < 4; ixstart++) {
+    b_y1[ixstart] = numer[ixstart] / fv2[0];
+  }
+
+  /*  Output 1 */
+}
+
+boolean_T rtIsNaNF(real32_T value){
+#if defined(_MSC_VER) && (_MSC_VER <= 1200)
+  return _isnan((real_T)value)? true:false;
+#else
+  return (value!=value)? 1U:0U;
+#endif
+}
diff -r 2245e978868c -r 84347af5a1f2 rtwtypes.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/rtwtypes.h	Sun Nov 01 18:38:43 2015 +0000
@@ -0,0 +1,159 @@
+/*
+ * rtwtypes.h
+ *
+ * Code generation for function 'IMU_Classifier'
+ *
+ */
+
+#ifndef __RTWTYPES_H__
+#define __RTWTYPES_H__
+#ifndef __TMWTYPES__
+#define __TMWTYPES__
+
+/*=======================================================================* 
+ * Target hardware information
+ *   Device type: Generic->MATLAB Host Computer
+ *   Number of bits:     char:   8    short:   16    int:  32
+ *                       long:  32    long long:  64
+ *                       native word size:  32
+ *   Byte ordering: LittleEndian
+ *   Signed integer division rounds to: Zero
+ *   Shift right on a signed integer as arithmetic shift: on
+ *=======================================================================*/
+
+/*=======================================================================* 
+ * Fixed width word size data types:                                     * 
+ *   int8_T, int16_T, int32_T     - signed 8, 16, or 32 bit integers     * 
+ *   uint8_T, uint16_T, uint32_T  - unsigned 8, 16, or 32 bit integers   * 
+ *   real32_T, real64_T           - 32 and 64 bit floating point numbers * 
+ *=======================================================================*/
+
+typedef signed char int8_T;
+typedef unsigned char uint8_T;
+typedef short int16_T;
+typedef unsigned short uint16_T;
+typedef int int32_T;
+typedef unsigned int uint32_T;
+typedef long long int64_T;
+typedef unsigned long long uint64_T;
+typedef float real32_T;
+typedef double real64_T;
+
+/*===========================================================================* 
+ * Generic type definitions: real_T, time_T, boolean_T, int_T, uint_T,       * 
+ *                           ulong_T, ulonglong_T, char_T and byte_T.        * 
+ *===========================================================================*/
+
+typedef double real_T;
+typedef double time_T;
+typedef unsigned char boolean_T;
+typedef int int_T;
+typedef unsigned int uint_T;
+typedef unsigned long ulong_T;
+typedef unsigned long long ulonglong_T;
+typedef char char_T;
+typedef char_T byte_T;
+
+/*===========================================================================* 
+ * Complex number type definitions                                           * 
+ *===========================================================================*/
+#define CREAL_T 
+   typedef struct {  
+      real32_T re;  
+      real32_T im;  
+   } creal32_T;  
+
+   typedef struct {  
+      real64_T re;  
+      real64_T im;  
+   } creal64_T;  
+
+   typedef struct {  
+      real_T re;  
+      real_T im;  
+   } creal_T;  
+
+   typedef struct {  
+      int8_T re;  
+      int8_T im;  
+   } cint8_T;  
+
+   typedef struct {  
+      uint8_T re;  
+      uint8_T im;  
+   } cuint8_T;  
+
+   typedef struct {  
+      int16_T re;  
+      int16_T im;  
+   } cint16_T;  
+
+   typedef struct {  
+      uint16_T re;  
+      uint16_T im;  
+   } cuint16_T;  
+
+   typedef struct {  
+      int32_T re;  
+      int32_T im;  
+   } cint32_T;  
+
+   typedef struct {  
+      uint32_T re;  
+      uint32_T im;  
+   } cuint32_T;  
+
+   typedef struct {  
+      int64_T re;  
+      int64_T im;  
+   } cint64_T;  
+
+   typedef struct {  
+      uint64_T re;  
+      uint64_T im;  
+   } cuint64_T;  
+
+
+/*=======================================================================* 
+ * Min and Max:                                                          * 
+ *   int8_T, int16_T, int32_T     - signed 8, 16, or 32 bit integers     * 
+ *   uint8_T, uint16_T, uint32_T  - unsigned 8, 16, or 32 bit integers   * 
+ *=======================================================================*/
+
+#define MAX_int8_T      ((int8_T)(127))
+#define MIN_int8_T      ((int8_T)(-128))
+#define MAX_uint8_T     ((uint8_T)(255))
+#define MIN_uint8_T     ((uint8_T)(0))
+#define MAX_int16_T     ((int16_T)(32767))
+#define MIN_int16_T     ((int16_T)(-32768))
+#define MAX_uint16_T    ((uint16_T)(65535))
+#define MIN_uint16_T    ((uint16_T)(0))
+#define MAX_int32_T     ((int32_T)(2147483647))
+#define MIN_int32_T     ((int32_T)(-2147483647-1))
+#define MAX_uint32_T    ((uint32_T)(0xFFFFFFFFU))
+#define MIN_uint32_T    ((uint32_T)(0))
+#define MAX_int64_T ((int64_T)(9223372036854775807LL))
+#define MIN_int64_T ((int64_T)(-9223372036854775807LL-1LL))
+#define MAX_uint64_T    ((uint64_T)(0xFFFFFFFFFFFFFFFFULL))
+#define MIN_uint64_T    ((uint64_T)(0ULL))
+
+/* Logical type definitions */
+#if !defined(__cplusplus) && !defined(__true_false_are_keywords)
+#  ifndef false
+#   define false (0U)
+#  endif
+#  ifndef true
+#   define true (1U)
+#  endif
+#endif
+
+/*
+ * Maximum length of a MATLAB identifier (function/variable)
+ * including the null-termination character. Referenced by
+ * rt_logging.c and rt_matrx.c.
+ */
+#define TMW_NAME_LENGTH_MAX 64
+
+#endif
+#endif
+/* End of code generation (rtwtypes.h) */