from Alpes.Specification import *
from Alpes.Prosthesis import AlpesProsthesis
import time
h = AlpesProsthesis()
h.initialise()
# Start flexing fingers
h.write_positions([5000, 19000, 40000, 40000, 40000, 40000])
# Reading while fingers are moving
print('Flexsion: reading motor positions and velocities ...')
for i in range(25):
print('Pos.: %s, Vel.: %s' % (h.read_positions(), h.read_velocities()))
time.sleep(0.1)
# Start extending fingers
h.write_positions([0, 0, 0, 0, 0, 0])
# Reading while fingers are moving
print('Extension: reading motor positions and velocities ...')
for i in range(25):
print('Pos.: %s, Vel.: %s' % (h.read_positions(), h.read_velocities()))
time.sleep(0.1)
# Positions are measured in encoder ticks.
# Velocities are measured in rpm of the motor shaft after reduction.
# thresholds are approximately measure as percentage of total muscle contraction.
# thresholds[0] corresponds to flexors, thresholds[1] correspons to extensors.
thresholds=[10, 15],
# cc_lock_duration filters out some unwanted control decisions after a co-contraction.
# cc_lock_duration is measured in number of 'winlen's (see variable above).
# Increase cc_lock_duration if unwanted motions appear after co-contraction or if
# co-contraction gets detected twice instead of once in a short amount of time.
cc_lock_duration=1)
grasps = [GRASPS().CYLINDRICAL, GRASPS().LATERAL, GRASPS().PINCH]
grasp = 0
# Connect the hand to the computer and switch it on. First run after connection
# will initialise the hand. Consecutive runs won't.
p = AlpesProsthesis()
p.initialise()
p.set_grasp(grasps[grasp])
mav2command = [0.02, 0.02
] #mapping from mean absolute signal to the control variable.
with hub.run_in_background(listener):
print('Streaming EMG ... Press ctrl-c or shift-c to stop.')
while hub.running:
time.sleep(winsec)
# Pull recent EMG data from the buffer
emg_data = listener.get_emg_data()
# Transform it to numpy matrix
emg_data = np.array([[x[1][flexors_chan], x[1][extensors_chan]]
for x in emg_data])
# Interpret EMG, produce decision
decision, mav = mc.decide(emg_data)