Add new attribute to the input of nerual network
When adding an attribute, increase the number of neurons in the input layer, then train the network again.

Having 100% accuracy may indicate that the model suffers over-fitting. To solve the problem:

1- make sure that the model doesn't see the test set at training time

2- If you have sufficient number of records, I would recommend going for K-folds validations rather than leave-one out cross-validation (for example 70% training 30% testing)

3- if the number of records is insufficient, (such as in your case: 38 records at best won't allow you go deep), either 


try to get more more data
or simplify your model (maybe just 1-2 layers with 1-3 neurons!)
or try machine learning methods other than neural networks. plz see (https://www.cs.sfu.ca/~jpei/publications/Sequence%20Classification.pdf).