Problems on reading PCM into digital form

Question

Hi,
I'm now on a project doing heart rate detection.
Due to the project just started, therefore I do not got any device to measure my own heart rate, but I will be making up some PCM(analog) data, and try to read that into digital form and give me results of the heart rate.
I'm not sure am I on the right track now or not,
what I'm doing now is trying to convert a ".wav" into bytes array, then it should give me some data, however, I'm not sure how to relate that data into heart rate.
Please leave me any comment if u think it might help please.
Thanks,
till

Answer 1

I'm not too sure what should be the .wav should be, however, according to this acticle I got it from the web:
_2.1 Signal acquisition_
ECG signal frequency content lies between about 0.05Hz and
500Hz and has amplitude of few mV. The acquisition is provided
to be performed in three different ways: (i) using direct electrode
measurements, (ii) using ECG equipment with analogous output;
and (iii) using ECG equipment with digital output. For the first
two cases, a sampling rate of 8 kHz is assumed. In the third case,
the acquired discrete signals are accordingly resampled.
_2.2 Modulation_
The bandwidth of the phone’s voice channel is limited to the
range 300Hz-3300Hz. The signal amplitude at the microphone
input should not exceed 100mV. Modulation is performed through
multiplication with carrying sinusoidal signals. Five 500Hz-wide
channels are packed within the 500Hz-3000Hz band. The
resulting signal is appropriately refined in amplitude and directed
to the modulator’s output.
_2.3 Digitizing, storing and sending_
The complex signal is band-limited to 3300Hz. Therefore, a
standard sampling frequency of 8 kHz is used for its digitization.
A JAVA application performs that and in order to store the signal
intact, the signal is recorded in a lossless format such as pulsecode
modulation (PCM). The WAV audio file format implements
PCM and is used to store the recorded modulated ECG signals.
Once stored, the signals can be visualized, processed and sent by
the mobile phone.
Mobile phone’s firmware is accessible by programming
languages as C++ and JavaTM. Most mobile phones support
JavaTM runtime called Kilobyte Virtual Machine (KVM) [6]. This
language provides the ability to build a GUI application that could
support all the stages of recording, storing and transmitting of the
ECG signal. JSR-135 contains libraries of JavaME, which are
useful for capturing audio from the microphone's port of a mobile
phone. The above mentioned platform was used to create the
application software.
_2.4 Demodulation_
The procedure of demodulation is performed at the physician’s
phone, following the reverse track of modulation. A digital band
pass filter is used to separate the spectra, corresponding to the
individual ECG signals. The filtered signal was then multiplied by
the corresponding carrier frequency and filtered with a low pass
filter, resulting in the original signal. The demodulated signals can
be stored in separate WAV files in the physician’s phone.
_2.5 Matlab simulations_
In order to prove the principal feasibility of the approach, the
signal acquisition, processing and transmission procedures were
simulated in MATLAB. Five preliminary recorded ECG signals
were directly loaded and used. The signals acquisition parameters
were: 8-bit values, sampling rate of 250Hz and duration – 10S.
Modulation and demodulation were programmed and performed
in a numerical way. Modulation was done by multiplication of the
ECG signals with carrying sinusoidal signals of frequencies
500Hz, 1000Hz, 1500Hz, 2000Hz, and 2500Hz. The
demodulation included first separating the spectrum of each
individual signal with the help of 4-th order 400Hz-wide bandpass
Butterword filters centered on the corresponding carrying
frequency. Next the filtered signals were multiplied with the same
carrier signals and eventually filtered with a low pass 4-th order
Butterworth filter (fc=200Hz).
btw, the system need to be implement into Symbian phone at the end,
but I'm just now testing on the PC atm =)
according to this article, what kind of wav I should be using ??
thanks a lot!!!