Research on Health Risk due to Impulsive Noise and Vibrations

1. Research on Health Risk due to Impulsive Noise and Vibrations Research Results Conducted in Collaboration with NIOSH Professor Jay Kim Students: Xiangdong Zhu, Wonjoon Song University of Cincinnati March 2006

2. Presentation Overview • Background • Analytic Wavelet Transform as the Basic Signal Analysis Tool for Impulsive Events • Hearing Loss Due to Impulsive Sound • Current work • Long-term approach • Hand Arm Vibration Syndrome (HAVS) • Some preliminary results • Planned approach • Other Applications of AWT • Gunshot data/ear protector analysis • AWT based rotating systems analysis

3. Background: Conducting NIOSH-UC power tool research consortium, lack of method for assessment of exposure risk to impulsive noise and vibrations • Impulsive Noise Induced Hearing Loss (INIHL) • Complex noise environment in workplaces • Military noises • Hand-Arm Vibration Syndrome (HAVS) due to impulsive vibrations • Current codes are based on steady-state metrics ignoring temporal variation of spectral characteristics Measured noise from power wrench

4. Issues in Risk Assessment of Impulsive Noise and Vibrations • Inherent difficulties of transient events • More parameters are necessary to characterize the event • Difficult to formulate metric and relate it to experimental or demographic study results • Characterization technique: time-frequency analysis is necessary • Wavelet analysis should be a choice, but nearly entire existing practices and data are based on Fourier quantities • Analytic Wavelet Transform (AWT): a hybrid of wavelet and FFT that works like a superb transient FFT analysis. All Fourier definitions, SPL, frequency spectra, can be defined in transient sense.

5. Current Status (1/2): Impulsive Noise • Impulsive Noise: • Current standards (OSHA, NIOSH, European standards) are based on equal energy hypothesis (85 dB, 6 dB exchange rule) • Use of dBA is considering spectral information • Temporal information is considered in very limited sense through allowable maximum peak SPL • Temporal variation of frequency spectrum is not considered • Research efforts to reflect temporal variations: • AHAAH model by Price and Kalb: time domain simulation of human ear • Chinchilla based study on INIHL by Hamernik et. al. • Expose chinchillas to steady-state and impulsive/complex noise • Used Kurtosis as the metric to represent temporal variations

6. Current Status (2/2): Impulsive Vibrations • Impulsive Vibrations: • Similar to INIHL cases because of the transient nature, but dissimilar because hand and arm do not have spatial frequency sensor as the hearing organ • Group of researchers at NIOSH Morgantown • Established frequency weightings for hand-arm vibrations and finger vibrations • Developed standard test procedures, numerical models, demographic study and theoretical background • Collaboration with UC is embarked in applying AWT and transient analysis technique to HAVS

7. picks up fast, high-frequency components picks up slow, low-frequency components Analytic Wavelet Transform (AWT): brief background (1/2) • Use variable time-frequency atom: source of the main advantage of wavelet analysis for transient signals Problems Works in un-familiar terms to engineers and scientists: scale, wavelet intensity, etc. instead of frequency and amplitude

8. Analytic Wavelet Transform (AWT): brief background (2/2) • Hybrid of wavelet transform and Fourier transform • Work in terms of traditional Fourier variables: frequency, amplitude and phase, however all as functions of time • A perfect replacement of Short-time Fourier transform (STFT) for transient analysis Our version of AWT is set up so that each AWT provides a time history of 1/3 octave component of center frequency of

9. AWT: application example(1/2) Inst. 1/3 octave spectrum 1/3 octave time history AWT Impulsive sound, time domain STFT T-F representation by AWT with cochlea mapping T-F representation by STFT Superiority of AWT compare to STFT is clear

10. AWT: application example(2/2) Airbag sound T-F plot 1/3 octave time histories

11. Hearing Loss due to Impulsive Sound (1/3): Current approach in pending NIH proposal Human NIHL model Chinchilla NIHL model Proposed research Chinchilla Test Data at SUNY-Plattsburgh Statistical correlation study to choose the best metric T-F noise metrics Digitized Noise data AWT Various, controlled noise set TTS, PTS, IHC and OHC loss data as functions of frequency About 400 Chinchillas Existing data

12. Hearing Loss due to Impulsive Sound (2/3): long-term plan Ear simulation model output (basilar membrane displacement) Chinchilla ear model Necessary development Inter-species scaling law Human ear model Ear simulation model output Human NIHL model Environmental Noise noise metric AWT Final form of implementation NIHL risk

13. Hearing Loss Due to Impulsive Sound: long-term plan (3/3):Develop inter-species scaling law Model output (basilar membrane displacement) Simulation ear model for chinchillas development Test Noise Data use Chinchilla NIHL model Inter-species scaling law Simulation ear model for cats Model output Compare to validate Simulated cat NIHL data Repeat NIHL model development for cats using cat experiment data Cat NIHL model Confirm scaling law

14. O u t e r E a r I n n e r E a r M i d d l e E a r V e s t i b u l a r D i f f r a c t i o n A n n u l a r V o l u m e A i r E a r d r u m s o u n d E a r c a n a l l i g a m e n t P l u g c o n d u c t i v e p a r t f i e l d S t a p e s I n c u s C o n c h a R p l C o c h l e a L 1 L 2 L 3 C a l R a l L v l e n g t h 1 : N t L i L s L d m C d c R d c R d f U e U c A 1 A 2 A 3 a r e a L d s L o L d f C m i C i s L p l P c R c R h C d s P e L h C b 2 P R o C r w P R m i R i s R d s C m H e l i c o t r e m a I n c u d o - R o u n d M a l t e o - L e v e r E a r d r u m s t a p e d a l w i n d o w a n d a r e a I n c u d a l i n d e p e n d e n t B u l l a j o i n t r a t i o j o i n t p a r t Example of Ear Model: AHAAH model developed by Price and Kalb

15. Hand Arm Vibration Syndrome (1/3) Time series T-F representation with ISO HA frequency weighting T-F representation with one of frequency weightings proposed for fingers

16. Hand Arm Vibration Syndrome (2/3) Frequency weighted time history: reflects what hand arm feel Sum frequency components at each time point

17. Hazard dose curve HAVS threshold acceleration level Metric based on frequency weighted time history Hand Arm Vibration Syndrome (3/3) Non-linear metric function Threshold level

18. Gunshot sound analysis Inside of ear protector Reduce SPL Outside of ear protector

19. Other Interesting Application: AWT based Campbell diagram AWT based Campbell Diagram Fourier transform based Campbell Diagram Rotating system start-up analysis In-situ FRF construction without excitation

20. Questions/Suggestions?