stoy tratando de construir un modelo RNN / LSTM para la clasificación binaria 0 o 1

una muestra de mi conjunto de datos (número de paciente, tiempo en molino / seg., normalización de X Y y Z, curtosis, asimetría, inclinación, balanceo y guiñada, etiqueta) respectivamente.

1,15,-0.248010047716,0.00378335508419,-0.0152548459993,-86.3738760481,0.872322164158,-3.51314800063,0

1,31,-0.248010047716,0.00378335508419,-0.0152548459993,-86.3738760481,0.872322164158,-3.51314800063,0

1,46,-0.267422664673,0.0051143782875,-0.0191247001961,-85.7662354031,1.0928406847,-4.08015176908,0

1,62,-0.267422664673,0.0051143782875,-0.0191247001961,-85.7662354031,1.0928406847,-4.08015176908,0 

lo que he intentado.

import numpy as np
from keras.datasets import imdb
from keras.models import Sequential
from keras.layers import Dense
from keras.layers import LSTM
from keras.layers import Bidirectional
from keras.preprocessing import sequence
# fix random seed for reproducibility
np.random.seed(7)

train = np.loadtxt("featwithsignalsTRAIN.txt", delimiter=",")
test = np.loadtxt("featwithsignalsTEST.txt", delimiter=",")

x_train = train[:,[2,3,4,5,6,7]]
x_test = test[:,[2,3,4,5,6,7]]
y_train = train[:,8]
y_test = test[:,8]

# create the model
model = Sequential()
model.add(LSTM(20, dropout=0.2, input_dim=6))
model.add(Dense(4, activation = 'sigmoid'))
model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
model.fit(x_train, y_train, epochs = 2)

pero me da el siguiente error

Error al verificar la entrada: se esperaba que lstm_1_input tuviera 3 dimensiones, pero obtuve una matriz con forma (1415684, 6)