Department of Electronic Engineering

Permanent URI for this collectionhttps://cris.hit.ac.zw/handle/123456789/10

Browse

Filters

2012 - 2019112020 - 20267

Settings

Search Results

Now showing 1 - 10 of 18
  • No Thumbnail Available
    Item
    Robotics Technology
    (HIT, 2026-06-25) HIT
  • No Thumbnail Available
    Item
    Intelligent System
    (HIT, 2026-06-22)
  • No Thumbnail Available
    Item
    Energy Systems Technologies
    (HIT, 2026-06-22) HIT
  • No Thumbnail Available
    Item
    Software Engineering and Applications
    (HIT, 2026-06-22) HIT
  • No Thumbnail Available
    Item
  • No Thumbnail Available
    Item
    Electronic Instrumentation Sytems
    (HIT, 2026-06-22) HIT
  • No Thumbnail Available
    Item
    Biomedical Signal Processing
    (HIT, 2025-11-25) HIT
  • Thumbnail Image
    Item
    Examination of Mel-frequency Cepstral Coefficients features for Parkinson's Disease telediagnosis
    (30th GISFI Standardisation Series Meeting and IEEE 5G Summit,, 2017-11-16) Masunda, Sam; Harisudha, Kuresan; Samiappan, Dhanalakshmi
    The focus for 5G networks is on high fidelity networks with extreme precision, making complete telediagnostic and telehealth realizations a possibility. The characterization of Parkinson’s disease (PD) is based on motor and non-motor functions of the body. Speech issues in PD patients identify with motor control, not to lost the phonetic learning required to make prosodic qualifications. Speech discourse issues are referred to as one of the most punctual markers for PD and clinical conclusion takes up to five years to identify PD. This means s pitch can be used as one of the biomarkers for PD. Attention is given to prosodic, spectral, vocal tract and excitation source speech features. Fundamental frequency, Pitch Period Entropy (PPE), jitter, shimmer, Melfrequency Cepstral Coefficients (MFCC) and Hidden Markov Model (HMM) are the parameters used in this respect
  • Thumbnail Image
    Item
    Development of a wearable wireless body area network for health monitoring of the elderly and disabled
    (IOP Conference Series: Materials Science and Engineering, 2017) Rushambwa, Munyaradzi C; Gezimati, Mavis; Jeeva, J B
    Novel advancements in systems miniaturization, electronics in health care and communication technologies are enabling the integration of both patients and doctors involvement in health care system. A Wearable Wireless Body Area Network (WWBAN) provides continuous, unobtrusive ambulatory, ubiquitous health monitoring, and provide real time patient’s status to the physician without any constraint on their normal daily life activities. In this project we developed a wearable wireless body area network system that continuously monitor the health of the elderly and the disabled and provide them with independent, safe and secure living. The WWBAN system monitors the following parameters; blood oxygen saturation using a pulse oximeter sensor (SpO2), heart rate (HR) pulse sensor, Temperature, hydration, glucose level and fall detection. When the wearable system is put on, the sensor values are processed and analysed. If any of the monitored parameter values falls below or exceeds the normal range, there is trigger of remote alert by which an SMS is send to a doctor or physician via GSM module and network. The developed system offers flexibility and mobility to the user; it is a real time system and has significance in revolutionizing health care system by enabling non-invasive, inexpensive, continuous health monitoring
  • Thumbnail Image
    Item
    Analysis of Jitter and Shimmer for Parkinson’s Disease Diagnosis Using Telehealth
    (International Conference on Cognitive Informatics & Soft Computing (CISC-2017), 2017-12-20) Kuresan, Harisudha; Masunda, Sam; Samiappan, Dhanalakshmi
    The future of telecommunications is premised on high fidelity net-works with extreme precision, which in turn capacitates deployment of tele-diagnostic tools. Parkinson’s disease (PD) clinical characterization is based on, speech problems, tremors in hands, arms, legs and face, body swelling, muscle rigidity and movement problems. Speech problems are cited as one of the earliest prodromal for PD. However, using clinical diagnosis it takes upto five or more years to detect PD. Therefore with this regard speech can be used as an early biomarker for PD. Features of interest for detecting PD will be prosodic, spectral, vocal tract and excitation source speech features. We infer from the analysis, MFFC with jitter and shimmer feature extraction provides a promising method that can help the clinicians in diagnostic process.