Correlations between Inertial Body Sensor Measures and Clinical Measures in Multiple Sclerosis
Journal Title: EAI Endorsed Transactions on Internet of Things - Year 2016, Vol 2, Issue 7
Abstract
Gait assessment using inertial body sensors is becoming popular as an outcome measure in multiple sclerosis (MS) research, supplementing clinical observations and patient-reported outcomes with precise, objective measures. Although numerous research reports have demonstrated the performance of inertial measures in distinguishing healthy controls and MS subjects, the relationship between these measures and the impact of MS on gait impairment remains poorly understood. In contrast, although clinical evaluation has limited variability in scores, it is meaningful and interpretable for clinicians. Therefore, this paper investigates correlations between two inertial measures and three clinical measures of walking ability. The clinical measures are the MS Walking Scale (MSWS-12), the Expanded Disability Status Scale (EDSS), and the six minute walk (6MW) distance. The inertial measures are the double stance time to single stance time ratio (DST/SST) and the causality index, both of which have been proven effective in MS gait assessment in previous work. 28 MS subjects and 13 healthy controls were recruited from an MS outpatient clinic. Most correlations among measures were strong and significant. Experimental results suggested that combining all five measures may improve separability performance for tracking MS disease progression.
Authors and Affiliations
Jiaqi Gong, Matthew Engelhard, Myla Goldman, John Lach
Keywords
Related Articles
- EP ID EP46483
- DOI http://dx.doi.org/10.4108/eai.28-9-2015.2261504
- Views 309
- Downloads 0
Securing the Timestamping of Sensor Data from Wearable Healthcare Devices
An ageing population, coupled with increasing prevalence of chronic diseases, is placing unsustainable demands on current healthcare systems. Home-based medical monitoring, supported by wearable sensors for heart-rate, E...
Semantic Interoperable Traffic Management Framework for IoT Smart City Applications
Real-time traffic monitoring and controlling are one of the biggest problems in this present living world. So many researchers have dealt with and put their effort into this problem, as a result, several types of approac...
FREACSIM - A Framework for Creating and Simulating Real-Time Capable Network on Chip Systems and Applications
This paper presents the new Framework for Real-time capable Embedded system and ArChitecture SIMulation (FREACSIM), a highly configurable full-system simulation environment enabling and easing the modeling, simulation an...
Driver’s ECG Signal Detection and Transmission by Impulse-Radio-Based Human Body Communication Technology
In this study, we developed a wearable electrocardiogram (ECG) sensor with human body communication (HBC) tech- nology for vital data transmission in a car. The ECG signals were modulated with wideband pulse signals betw...
Parkinson’s disease as a Working Model for Global Healthcare Restructuration: The Internet of Things and Wearables Technologies
With the rapid growth and increased life expectancy of the world’s population, the prevalence of chronic disorders such as Parkinson’s disease (PD) is also increasing. This challenges the current healthcare system in ter...