Keras fit_generator() for long signals
I found a solution to this problem with some good help from this article.
What I found really convenient is to make two generators. One for features, or X, and one for labels, or y.

def generate_X():
    while True:
        with open("/mypath/myData.csv") as f:
            for line in f:
                x= line.rstrip('\n').split(",")
                x= np.asarray(x)
                x=x[1:]
                x= x.reshape(1,1,12)
                yield x



def generate_y():
    while True:
        for i in range(len(y_train)):
            y= y_train[i]
            yield y


And then I go ahead and use these two generators as input to my third generator which will make batches of a desired size to the fit_generator()

def batch_generator(batch_size, gen_x,gen_y): 

    batch_features = np.zeros((batch_size,1, 12))
    batch_labels = np.zeros((batch_size,9))

    while True:
        for i in range(batch_size):
            batch_features[i] = next(gen_x)
            batch_labels[i] = next(gen_y)
        yield batch_features, batch_labels


And last, but not least I am now able to use the batch_generator when training my model

model.fit_generator(batch_generator(128, generate_X(), generate_y()),
                    steps_per_epoch=(len(y_train)/128), epochs=2, verbose=1)