import numpy as np
[docs]def upperArm_score(header, data):
"""returns rula score for upper Arm
takes all three anatomical angles for shoulder provided by MR3s myoMOTION
"""
# No. 1 of RULA protocol
angle_limits = [[-20, 20], [-20, 20, 45], [45, 90], [90]] # rula definition
angle_abdu = 30 # own definition/limit
shoulder_flex = np.zeros((len(data), 2)) # [0,1 == left, right]
shoulder_abdu = np.zeros((len(data), 2)) # [0,1 == left, right]
shoulder_flex[:, 0] = data[:, np.where(header == "Schulter Flexion LT,Grad")[0][0]]
shoulder_flex[:, 1] = data[:, np.where(header == "Schulter Flexion RT,Grad")[0][0]]
shoulder_abdu[:, 0] = data[:, np.where(header == "Schulter Abduktion LT,Grad")[0][0]]
shoulder_abdu[:, 1] = data[:, np.where(header == "Schulter Abduktion RT,Grad")[0][0]]
score_left = np.zeros((len(data), 1)) # [0,1 == angleScore, additional]
score_right = np.zeros((len(data), 1)) # [0,1 == angleScore, additional]
for a in range(len(data)):
# scoring for left side
if shoulder_flex[a, 0] > angle_limits[0][0] and shoulder_flex[a, 0] <= angle_limits[0][1]:
score_left[a, 0] = 1
elif shoulder_flex[a, 0] < angle_limits[1][0]:
score_left[a, 0] = 2
elif shoulder_flex[a, 0] > angle_limits[1][1] and shoulder_flex[a, 0] <= angle_limits[1][2]:
score_left[a, 0] = 2
elif shoulder_flex[a, 0] > angle_limits[2][0] and shoulder_flex[a, 0] <= angle_limits[2][1]:
score_left[a, 0] = 3
elif shoulder_flex[a, 0] > angle_limits[3][0]:
score_left[a, 0] = 4
# scoring for right side
for b in range(len(data)):
if shoulder_flex[b, 1] > angle_limits[0][0] and shoulder_flex[a, 0] <= angle_limits[0][1]:
score_right[b, 0] = 1
elif shoulder_flex[b, 1] < angle_limits[1][0]:
score_right[b, 0] = 2
elif shoulder_flex[b, 1] > angle_limits[1][1] and shoulder_flex[a, 0] <= angle_limits[1][2]:
score_right[b, 0] = 2
elif shoulder_flex[b, 1] > angle_limits[2][0] and shoulder_flex[a, 0] <= angle_limits[2][1]:
score_right[b, 0] = 3
elif shoulder_flex[b, 1] > angle_limits[3][0]:
score_right[b, 0] = 4
abucted_arm_left = np.where(shoulder_abdu[:, 0] > angle_abdu)[0]
abucted_arm_right = np.where(shoulder_abdu[:, 1] > angle_abdu)[0]
score_left[abucted_arm_left, 0] += 1
score_right[abucted_arm_right, 0] += 1
print("\n???????????????\nQUESTION\n???????????????")
while True:
try:
a = int(input(
"Wie lange ist die Person angelehnt ODER\n der Arm unterstützt?\n [Angabe in % relativ zur Gesamtdauer des Vorgangs]\n\n\t"))
a = a / 100
break
except ValueError:
print("Oppsidaysi! That wasn't an integer Value. Try again!")
print('upper Arm:')
print(np.mean(score_left[:, 0]))
print(np.mean(score_right[:, 0]))
return score_left, score_right
