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

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...

Optimal sleep-state control of energy-aware M/G/1 queues

We study the problem of optimally controlling the use of sleep states in an energy-aware M/G/1 queue. In our model, we consider a family of policies where the server upon becoming idle can wait for a random period before...

BLE or IEEE 802.15.4: Which Home IoT Communication Solution is more Energy-Efficient?

IEEE 802.15.4 (used by Zigbee, 6LoWPAN and Thread) and Bluetooth Low Energy (BLE) are two widely used wireless standards for ultra low power IoT (Internet of Things) technologies and smart home applications. In this arti...

An iterative Power Allocation Alogrithm for Energy Efficiency Optimization in Massive MIMO Systems

In this paper, a transmitting power allocation strategy for users jointed together pre-coding is presented to eliminate inter-users interference and improve the energy efficiency of Massive MIMO systems. The power alloca...

Secure ID-Based Routing for Data Communication in IoT

Internet of Things is rising technology that could inspire the way wireless network access is provided. In IoT, secure data communication has lot of research scope. Especially message authentication, authorization cure p...

Download PDF file
  • EP ID EP46483
  • DOI http://dx.doi.org/10.4108/eai.28-9-2015.2261504
  • Views 267
  • Downloads 0

How To Cite

Jiaqi Gong, Matthew Engelhard, Myla Goldman, John Lach (2016). Correlations between Inertial Body Sensor Measures and Clinical Measures in Multiple Sclerosis. EAI Endorsed Transactions on Internet of Things, 2(7), -. https://europub.co.uk/articles/-A-46483