, Biomedical Signal Processing and Control, Volume 71, January 2022
A cerebrovascular accident or stroke is the second commonest cause of death in the world. If it is not fatal, it can result in paralysis, sensory impairment and significant disability. Rehabilitation plays an important role to help survivors relearn lost skills and assist them to regain independence and thus ameliorate their quality of life. With the development of technology, researchers have come up with new solutions to assist clinicians in monitoring and assessing their patients; as well as making physiotherapy available to all.
, Medical Image Analysis, Volume 67, January 2021
The enormous social and economic cost of Alzheimer's disease (AD) has driven a number of neuroimaging investigations for early detection and diagnosis. Towards this end, various computational approaches have been applied to longitudinal imaging data in subjects with Mild Cognitive Impairment (MCI), as serial brain imaging could increase sensitivity for detecting changes from baseline, and potentially serve as a diagnostic biomarker for AD. However, current state-of-the-art brain imaging diagnostic methods have limited utility in clinical practice due to the lack of robust predictive power.
, Biomedical Signal Processing and Control, Volume 62, September 2020
Objective imaging-based biomarker discovery for psychiatric conditions is critical for accurate diagnosis and treatment. Using a machine learning framework, this work investigated the utility of brain's functional network topology (complex network features) extracted from functional magnetic resonance imaging (fMRI) functional connectivity (FC) as viable biomarker of autism spectrum disorder (ASD). To this end, we utilized resting-state fMRI data from the publicly available ABIDE dataset consisting of 432 ASD patients and 556 matched healthy controls.
, Journal of Neuroscience Methods, Volume 337, 1 May 2020
Alzheimer's disease is the most common form of dementia and is a serious health problem. The disease is expected to increase further in the upcoming years with the increase of the elderly population. Developing new treatments and diagnostic methods is getting more important. In this study, we focused on the early diagnosis of dementia in Alzheimer's disease via analysis of neuroimages. We analyzed the data diagnosed by the Alzheimer's Disease Neuroimaging Initiative (ADNI) protocol.
, Biomedical Signal Processing and Control, Volume 57, March 2020
Clinical assessment of speech abnormalities in Cerebellar Ataxia (CA) is subjective and prone to intra- and inter-clinician inconsistencies. This paper presents an automated objective method based on a single syllable repetition task to detect and quantify speech-timing anomalies in ataxic speech. Such a technique is non-invasive, reliable, fast, cost-effective and can be used in the comfort of home without any professional assistance.
, Smart Health, Volume 9-10, December 2018
This work intends to develop an intelligent, four-dimensional (namely X-Y-Z plus somatosensory), partial control, and virtual-reality-enabled Tai-Chi System (VTCS). Tai-Chi is a traditional mind-body wellness and healing art, and its clinical benefits have been well documented. VTCS integrates Tai-Chi with a series of cutting-edge computer technologies including 4D sensor technology, big-data, signal processing and analysis, human body kinematics, deep learning, virtual reality, and 4D-reconstruction, etc.