Bob Huang | University of Oklahoma (original) (raw)
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The main goal of this thesis is to use the recording gauge for Chinese medical auscultation to c... more The main goal of this thesis is to use the recording gauge for Chinese medical
auscultation to classify and identify the voice signal between the healthy people
and the deficiency of vital energy patients.
The traditional Chinese medicine doctor uses the major methods of diagnosis
“observing, auscultation and smelling, enquiry and feeling patients’ pulse “to
discriminate and diagnose symptoms of a disease clinically. In listening
examination, the method used in diagnosis is divided into listening and smelling.
Because the diagnosis process usually needs to be judged by the Chinese
medicine doctor with enough clinical experience, it leads to the diagnosis which
is not objective. Up to now, the major study in listening examination still
emphasizes on analyzing patients’ voices.
We collected 63 patients’ voice samples (There were 52 healthy people and
11 deficiency of vital energy patients). We recorded the voice signals of English
vowel /a/ and let these signals to be analyzed by 4 deficiency of vital energy
disease parameters. We use the recording gauge for Chinese medical auscultation
to examine and record human data.
Our research uses the recording gauge for Chinese medical auscultation to
examine and record human data. The main structure of the recording gauge for
Chinese medical auscultation is based on MSP430 microprocessor. The recording
gauge for Chinese medical auscultation uses its microphone which can fix
distance to record voice signals of healthy people and patients, establishes signal
files, then analyzes these data. We use four parameters(Average zero-crossing
rates, variations in local peaks and valleys, and Spectral energy ratio of high
frequency region and low frequency region ) to analyze signals and find
difference property of signals.
According to recognizing vital energy patients and healthy people, The voice
waveform of deficiency of vital energy patients is weaker than healthy people in
minor-wave intensity. We also find out that the power spectrum has clear
difference between the two voice waveform. As the analysis result, we came up
with a 76% accuracy comparing to physician’s diagnosis.
Keywords : auscultation,vital energy,voice analysis,the recording gauge for
Chinese medical auscultation
Roadway safety is a serious public health issue. Vehicle crashes on the roads and highways cost l... more Roadway safety is a serious public health issue. Vehicle crashes on the roads and highways cost loss of lives and damages to properties. Technology exists today to help identify and respond quickly to crashes, which is specially critical in rural areas. A feature that enables a car to warn its driver against an eminent crash or to recommend the proper speed based on traffic and weather conditions is much needed in todays Internet of Things (IoT) era. Connected Vehicle (CV) technologies are contributing towards fulfilling this need. In this paper, we present a safety driving system through a cooperative hazard awareness and avoidance (CHAA) system based on V2V (vehicleto-vehicle) and V2I (vehicle-to-infrastructure) communications. Our approach is based on DSRC-based V2V communications. It aims to alert drivers and recommend the proper speeds for vehicles that are approaching a hazardous zone due, for instance, to low visibility conditions. We also validate the proposed hazard alert and speed recommender system under various scenarios through simulations using the iTetris platform and SUMO simulator and we demonstrate its outperformance, compared to a regular environment, in terms of risk reduction and road safety efficiency. To this end, we have adapted iTetris by updating some of its existing features (like the Geo-broadcast routing capability) which is another contribution of this paper.
The main goal of this thesis is to use the recording gauge for Chinese medical auscultation to c... more The main goal of this thesis is to use the recording gauge for Chinese medical
auscultation to classify and identify the voice signal between the healthy people
and the deficiency of vital energy patients.
The traditional Chinese medicine doctor uses the major methods of diagnosis
“observing, auscultation and smelling, enquiry and feeling patients’ pulse “to
discriminate and diagnose symptoms of a disease clinically. In listening
examination, the method used in diagnosis is divided into listening and smelling.
Because the diagnosis process usually needs to be judged by the Chinese
medicine doctor with enough clinical experience, it leads to the diagnosis which
is not objective. Up to now, the major study in listening examination still
emphasizes on analyzing patients’ voices.
We collected 63 patients’ voice samples (There were 52 healthy people and
11 deficiency of vital energy patients). We recorded the voice signals of English
vowel /a/ and let these signals to be analyzed by 4 deficiency of vital energy
disease parameters. We use the recording gauge for Chinese medical auscultation
to examine and record human data.
Our research uses the recording gauge for Chinese medical auscultation to
examine and record human data. The main structure of the recording gauge for
Chinese medical auscultation is based on MSP430 microprocessor. The recording
gauge for Chinese medical auscultation uses its microphone which can fix
distance to record voice signals of healthy people and patients, establishes signal
files, then analyzes these data. We use four parameters(Average zero-crossing
rates, variations in local peaks and valleys, and Spectral energy ratio of high
frequency region and low frequency region ) to analyze signals and find
difference property of signals.
According to recognizing vital energy patients and healthy people, The voice
waveform of deficiency of vital energy patients is weaker than healthy people in
minor-wave intensity. We also find out that the power spectrum has clear
difference between the two voice waveform. As the analysis result, we came up
with a 76% accuracy comparing to physician’s diagnosis.
Keywords : auscultation,vital energy,voice analysis,the recording gauge for
Chinese medical auscultation
Roadway safety is a serious public health issue. Vehicle crashes on the roads and highways cost l... more Roadway safety is a serious public health issue. Vehicle crashes on the roads and highways cost loss of lives and damages to properties. Technology exists today to help identify and respond quickly to crashes, which is specially critical in rural areas. A feature that enables a car to warn its driver against an eminent crash or to recommend the proper speed based on traffic and weather conditions is much needed in todays Internet of Things (IoT) era. Connected Vehicle (CV) technologies are contributing towards fulfilling this need. In this paper, we present a safety driving system through a cooperative hazard awareness and avoidance (CHAA) system based on V2V (vehicleto-vehicle) and V2I (vehicle-to-infrastructure) communications. Our approach is based on DSRC-based V2V communications. It aims to alert drivers and recommend the proper speeds for vehicles that are approaching a hazardous zone due, for instance, to low visibility conditions. We also validate the proposed hazard alert and speed recommender system under various scenarios through simulations using the iTetris platform and SUMO simulator and we demonstrate its outperformance, compared to a regular environment, in terms of risk reduction and road safety efficiency. To this end, we have adapted iTetris by updating some of its existing features (like the Geo-broadcast routing capability) which is another contribution of this paper.