Start Date

5-2020 12:00 AM

Description

While myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is relatively new and poorly understood, a recent upsurge in research has identified the disease’s core symptoms, including post-exertional malaise and orthostatic intolerance. The FDA has yet to approve any treatments for ME/CFS, partially due to a lack of validated efficacy endpoints.

The central focus of this research is to develop ME/CFS efficacy endpoints using a non-invasive, inertial measurement-based approach. Accessible endpoints will provide a way to properly evaluate potential treatments for ME/CFS. Using a Kalman filter, inertial measurement unit (IMU) data can be converted to optimized leg angle estimates. These angle estimates can then be converted to personalized daily measurements of upright activity, referred to as uptime.

In a six-day, case-control study conducted by the Bateman Horne Center, uptime was measured for 15 subjects (five controls, five moderate-level ME/CFS, and five severe-level ME/CFS). Analysis of these uptime scores indicated that each group spends different proportions of their days upright and active. This result shows that uptime can accurately determine disease severity and is, therefore, a reliable endpoint for evaluating ME/CFS treatment efficacy.

Comments

Due to COVID-19, the Symposium was not able to be held this year. However, papers and posters were still submitted.

Available for download on Saturday, May 01, 2021

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May 1st, 12:00 AM

Development of an Inertial Measurement-Based Assessment of Disease Severity in Chronic Fatigue Syndrome

While myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is relatively new and poorly understood, a recent upsurge in research has identified the disease’s core symptoms, including post-exertional malaise and orthostatic intolerance. The FDA has yet to approve any treatments for ME/CFS, partially due to a lack of validated efficacy endpoints.

The central focus of this research is to develop ME/CFS efficacy endpoints using a non-invasive, inertial measurement-based approach. Accessible endpoints will provide a way to properly evaluate potential treatments for ME/CFS. Using a Kalman filter, inertial measurement unit (IMU) data can be converted to optimized leg angle estimates. These angle estimates can then be converted to personalized daily measurements of upright activity, referred to as uptime.

In a six-day, case-control study conducted by the Bateman Horne Center, uptime was measured for 15 subjects (five controls, five moderate-level ME/CFS, and five severe-level ME/CFS). Analysis of these uptime scores indicated that each group spends different proportions of their days upright and active. This result shows that uptime can accurately determine disease severity and is, therefore, a reliable endpoint for evaluating ME/CFS treatment efficacy.