“ Analyze reaction of newborn to music ”

“Analyze reaction of newborn to music ” Maslovsky Eugene Vainbrand Dmitri Instructor:Kirshner Hagai Winter 2005

Agenda • Concept • Available Raw Data • Project Goals • Analysis Techniques • Project Flow • Results • Conclusions • Future research

Concept • Observations of newborn show that music influences their behavior. • Our project is part of a research on reactions of newborn to different music styles. • Can Engineering Analysis methods add new views and maybe resolvethis issue?

Available Data • Six bio-signals were recorded from newborn while playing them music alternately: • Respiratory. • ECG. • EEG from four sources. • There is an online recorded movie.

Project Goals • Study characteristics of basic bio-signals. • Study different signal processing and statistical methods. • Analyze given medical signals and define their connection to music playing.

Analysis techniques • Signal processing basic methods: • DFT/FFT • Filtering • Window multiplying • Parameter estimation • AR model • Spectrogram • Statistical and Math methods: • Statistical hypothesis • Histograms

Project Flow • Analyzing ECG Signal • Visual analyze in time and frequency • Basic Parameters analysis • Analyzing ECG in time domain • Statistical analysis of Amplitude and periods • Typical period shape analysis • FECG • Analyzing Respiratory Signal • Visual analyze in time and frequency • Basic Parameters analysis • Analyzing AR model

First silent Second silent First music Third silent Second music Forth silent Third music Fifth silent First Silent Music Silent Definitions • Time segments

Results • ECG: • Visual • In time domain signal is periodical. • In frequency domain signal is modulated pulse train with 50Hz bandwidth but there are no suitable parameters to analyze. • Windowing didn’t give other visual information.

Result Mean energy: Music segments have slightly lower energy Hypothesis of equality - Denied with 0.99 probability

Results • Statistical analysis of R-Amplitude, HR and HRV • HR • Similar histograms • Equality hypothesis not denied • Conclusion: No influence detected • HRV • Similar histograms except firsts 2 silent segments vs. all others • But Equality hypothesis not denied • Conclusion: No influence detected • R-Amplitude mean • Similar histograms • Equality hypothesis not denied • Conclusion: No influence detected

Results • Statistical analysis of R-Amplitude, HR and HRV (cont) • R-Amplitude deviation • First two silent segments histogram is different • Equality hypothesis for First two silent segments vs. the others was denied with 98% C.L. • Conclusion: R-peaks amplitude became more unstable during the experiment. Can be related to music influence

Results • Typical period shape analysis • Averaging on all periods shapes of each segment • Bigger difference between 2 first and rest segments

Results Draft

Results • FECG • The purpose: “edge influence” detection on HR • No edge influence was detected

Results • Respiratory: • Visual impression: noise, no typical cyclicality, no typical amplitude. • Mean Energy: No results that show connection. • Signal processing: • There is a typical picture in frequency domain in 4Hz bandwidth but there no suitable parameters to analyze. • No effects from windowing and filtering. No visual correlation found.

Results (cont.) • Auto Regressive model fitting • Goal – Estimate Frequency spectrum with auto regressive model. • We couldn’t find suitable results. • Maximum peak frequency variation was totally random

Results (cont.) • Spectrogram analysis • No good visual results was achieved by spectrogram analysis

Thanks Thanks for your attention!

“ Analyze reaction of newborn to music ”