Butterworth filter in python
(Not an answer, but can't post code in a comment)

Works fine for me:

from

 __future__ import division
from numpy.random import randn
from numpy.fft import rfft
from scipy.signal import butter, lfilter
from matplotlib.pyplot import loglog

def butter_bandpass(lowcut, highcut, fs, order=5):
    nyq = 0.5 * fs
    low = lowcut / nyq
    high = highcut / nyq
    b, a = butter(order, [low, high], btype='band')
    return b, a

def butter_bandpass_filter(data, lowcut, highcut, fs, order=5):
    b, a = butter_bandpass(lowcut, highcut, fs, order=order)
    y = lfilter(b, a, data)
    return y

fs = 250
lowcut = 1.0
highcut = 50.0
x_Vtcr = randn(10000)
x2_Vtcr = butter_bandpass_filter(x_Vtcr, lowcut, highcut, fs, order=4)
loglog(abs(rfft(x_Vtcr)))
loglog(abs(rfft(x2_Vtcr)))


What do you get that's different from this?