objective measurement of fatigue

[Cece]

http://www.ncbi.nlm.nih.gov/pubmed/23151461

Physiol Meas. 2012 Dec;33(12):2033-48. doi: 10.1088/0967-3334/33/12/2033. Epub 2012 Nov 15.
A wireless body measurement system to study fatigue in multiple sclerosis.
Yu F, Bilberg A, Stenager E, Rabotti C, Zhang B, Mischi M.

Mads Clausen Institute, University of Southern Denmark, Alsion 2, Sønderborg, DK-6400, Denmark.

Abstract
Fatigue is reported as the most common symptom by patients with multiple sclerosis (MS). The physiological and functional parameters related to fatigue in MS patients are currently not well established. A new wearable wireless body measurement system, named Fatigue Monitoring System (FAMOS), was developed to study fatigue in MS. It can continuously measure electrocardiogram, body-skin temperature, electromyogram and motions of feet. The goal of this study is to test the ability of distinguishing fatigued MS patients from healthy subjects by the use of FAMOS. This paper presents the realization of the measurement system including the design of both hardware and dedicated signal processing algorithms. Twenty-six participants including 17 MS patients with fatigue and 9 sex- and age-matched healthy controls were included in the study for continuous 24 h monitoring. The preliminary results show significant differences between fatigued MS patients and healthy controls. In conclusion, the FAMOS enables continuous data acquisition and estimation of multiple physiological and functional parameters. It provides a new, flexible and objective approach to study fatigue in MS, which can distinguish between fatigued MS patients and healthy controls. The usability and reliability of the FAMOS should however be further improved and validated through larger clinical trials.

A way to objectively measure fatigue could demonstrate improvements in fatigue seen after the CCSVI procedure.

[munchkin]

It can continuously measure electrocardiogram, body-skin temperature, electromyogram and motions of feet.

This information will be very interesting to see as well and to see how they utilize the data beyond fatigue.