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Yuan-Ting Zhang

Publications and source records attributed to Yuan-Ting Zhang.

2 recordsLinked to original sources

Implementation of a WAP-based telemedicine system for patient monitoring.

Many parties have already demonstrated telemedicine applications that use cellular phones and the Internet. A current trend in telecommunication is the convergence of wireless communication and computer network technologies, and the emergence of wireless application protocol (WAP) devices is an example. Since WAP will also be a common feature found in future mobile communication devices, it is worthwhile to investigate its use in telemedicine. This paper describes the implementation and experiences with a WAP-based telemedicine system for patient-monitoring that has been developed in our laboratory. It utilizes WAP devices as mobile access terminals for general inquiry and patient-monitoring services. Authorized users can browse the patients' general data, monitored blood pressure (BP), and electrocardiogram (ECG) on WAP devices in store-and-forward mode. The applications, written in wireless markup language (WML), WMLScript, and Perl, resided in a content server. A MySQL relational database system was set up to store the BP readings, ECG data, patient records, clinic and hospital information, and doctors' appointments with patients. A wireless ECG subsystem was built for recording ambulatory ECG in an indoor environment and for storing ECG data into the database. For testing, a WAP phone compliant with WAP 1.1 was used at GSM 1800 MHz by circuit-switched data (CSD) to connect to the content server through a WAP gateway, which was provided by a mobile phone service provider in Hong Kong. Data were successfully retrieved from the database and displayed on the WAP phone. The system shows how WAP can be feasible in remote patient-monitoring and patient data retrieval.

Blood Pressure↗

The application of bionic wavelet transform to speech signal processing in cochlear implants using neural network simulations.

Cochlear implants (CIs) restore partial hearing to people with severe to profound sensorineural deafness; but there is still a marked performance gap in speech recognition between those who have received cochlear implant and people with a normal hearing capability. One of the factors that may lead to this performance gap is the inadequate signal processing method used in CIs. This paper investigates the application of an improved signal-processing method called bionic wavelet transform (BWT). This method is based upon the auditory model and allows for signal processing. Comparing the neural network simulations on the same experimental materials processed by wavelet transform (WT) and BWT, the application of BWT to speech signal processing in CI has a number of advantages, including: improvement in recognition rates for both consonants and vowels, reduction of the number of required channels, reduction of the average stimulation duration for words, and high noise tolerance. Consonant recognition results in 15 normal hearing subjects show that the BWT produces significantly better performance than the WT (t = -4.36276, p = 0.00065). The BWT has great potential to reduce the performance gap between CI listeners and people with a normal hearing capability in the future.

Cochlear Implants↗