# Causality between two binary time series

I have the following sample of a big dataframe:

Time (ms)  Signal_1  Signal_2
0          0         0
1          0         0
2          0         1
3          0         0
4          1         0
5          0         0
6          0         0
.          .         .
.          .         .
.          .         .
996        1         1
997        0         0
998        0         0


Signal_1 represents if occurred a heart beat in a person X in Time i.

Signal_2 represents if occurred a heart beat in a person Y in Time i.

Time (ms) is the Time i and the index of the dataframe. Time = 0 represents the begin of the experiment. Time = 1000 represents the first second passed after the begin of the experiment.

Since the signals are nominal (boolean), how can I use VAR and Granger Causality to say if Signal_1 causes Signal_2? Is there any way to calculate correlation between these binary time series data?

Thanks!