Pattern counting in time-series data

I have exercise data from an 3-axis accellerometer and a 3-axis gyroscope as time series. The exercise consists of one specific movement of the arm that is repeated with the sensors attached to the arm. A sample of the data is shown below. The first 3 columns is the gyro data and the last 3 columns are from the accellerometer:

2017/12/11 00:06:01 253.94  10.56   175.75  4.48    -3.18   -2.25
2017/12/11 00:06:02 254.5   41.5    166.5   0.72    -0.18   -2.86
2017/12/11 00:06:02 228.88  52.06   163.69  -0.38   -1.15   -1.67
2017/12/11 00:06:02 253.31  36.13   167.88  1.67    -0.35   -3.56
2017/12/11 00:06:02 253.88  -7.5    175.75  4.41    -0.16   -1.78
2017/12/11 00:06:03 244.94  -58.25  -173.81 3.62    -0.84   0.66
2017/12/11 00:06:03 240     -83.69  -174.5  0.94    -0.52   2.46
2017/12/11 00:06:03 236.88  -82.94  -124.5  2.23    -0.65   3.91
2017/12/11 00:06:03 255.19  -47.25  178.44  2.12    -2.42   -3.7

If I plot the data into excel I can see that there are patterns due to the recurring movement. Each axis of the sensors has his own pattern.

I want to be able to count the repetitions in .NET C# in this data. Which algorithm can be used to identify each repetition from 6 different sensory data ?