MSVirtual2020: Wearable technologies: where can we focus on next in MS

[ActiveMSers]

P0183 - Wearable technologies: where can we focus on next in Multiple Sclerosis? (ID 1126)

Speakers

• S. Alexander

Authors

• S. Alexander
• G. Peryer
• E. Gray
• F. Barkhof
• J. Chataway

Presentation Number
P0183
Presentation Topic
Clinical Outcome Measures

• Abstract

Background
Wearable technology refers to any sensor worn on the person, which as a result makes continuous and remote monitoring available to many people with chronic diseases, including multiple sclerosis (MS). Daily monitoring seems an ideal solution either as an outcome measure or as an adjunct to support rater-based monitoring in both clinical and research settings. There has been an increase in solutions that are available and we look to identify next generation wearables.

Objectives
To identify all validated wearable solutions for PwMS and identify areas of focus for wearable solutions in multiple sclerosis.

Methods
We completed a scoping review (using the PRISMA-ScR guidelines) to summarise the wearable solutions currently available in MS.

Our search strategy utilized subject heading searches: ‘Multiple Sclerosis’ and ‘wearable electronic devices’, as well as keywords ‘wearable technology’, and ‘electronic devices’. The literature search was conducted using MEDLINE (via PubMed) and Embase (via OVID) databases. This search included articles published from database inception to 30 May 2019. Additional searches looked at frequently published authors with different devices, as well as forward and backward citation tracking of included papers.

Results
We identified 35 validated unique solutions that measure gait, cognition, upper limb function, activity, mood and fatigue with most of these solutions being phone applications. Of these, 51% looked at lower limb function with activity levels being looked at by 37% of the total solutions. There was least focus on visual, and mood solutions at 3%, closely followed by quality of life and balance at 5%. Cognition and fatigue accounted for 14% of the total.

Conclusions
Looking forward, there is a change occurring from single measure solutions to multi-measure and multi-sensor solutions, such as the Floodlight Open app, which utilises multiple sensors within a smart-phone to remotely measure gait, cognition and upper limb function. Future research should consider costs and include implementation science as part of their research and design to ensure cost of delivery strategy is also accounted for.

As development in wearable technology in MS is still on-going, we can expect to see newer wearables focusing on other areas with technology advancements that allow for more upper body and cognitive measures. There is a dearth of validated solutions available for fatigue, mood, and pain.

[ActiveMSers]

P0888 - Multiple Sclerosis Patients' Perceptions of Using an Accelerometer and Mobile App for Clinical Research (ID 1464)

Speakers
M. Kossoff
Authors
M. Kossoff J. Ritter J. Keller E. Mowry K. Mendez
Presentation Number
P0888
Presentation Topic
Observational Studies

Abstract

Background
Designing data collection methods is a vital, yet challenging part of conducting multiple sclerosis (MS) clinical studies. Emerging technologies, such as wearable activity monitors (i.e. Accelerometers) and mobile applications (apps), provide innovative methods of objectively measuring MS patient outcomes. However, there is a gap in scientific knowledge about MS patients’ experiences with using these technologies in clinical research. This knowledge is imperative because patients’ perceptions of these technologies can affect adherence to study protocols. Research is needed to understand the feasibility of using these technologies for continuous long-term monitoring and data collection.

Objectives
To describe how persons living with MS perceived an accelerometer and diet-tracking app in a longitudinal clinical study and to apply this knowledge to the design and conduct of future clinical research.

Methods
This was a qualitative study nested in a larger observational study, which collected data using the Actigraph accelerometer and Calorie-Mama AI mobile app. Semi-structured qualitative interviews were conducted during final study visits (September 2018- March 2019), audio recorded, and transcribed verbatim. We continued interviewing participants until data saturation occurred. Qualitative data were analyzed using the constant comparative method. To further explore qualitative results, we did chi-squared tests to examine relationships between 1. age and successful diet tracking and 2. disability and interest in an MS self-management app.

Results
We interviewed 28 persons living with MS: 68% were female, mean age was 45.5 years, and median Expanded Disability Status Score (EDSS) was 2 (indicating low disability). Participants’ perceptions of the accelerometer were that it was “bulky” (n=21) and attracted unwanted attention (n=9), and that the band was uncomfortable (n=20). Participants (n=12) also mentioned they would have liked feedback from the device during or after the study. Despite stated issues, 93% of participants indicated they would use the device again in future studies. The mobile app was perceived as difficult to use to accurately track food (n=21) and time-consuming (n=10). As a result, half of participants did not correctly record their diet for the study. Younger age was associated with successful app use [X2 (1, N=27)= 4.46, p=0.035]. Also, many persons living with MS were interested in an MS self-management app, and interest was associated with higher EDSS [X2 (1, N=27)= 6.01, p=0.022].

Conclusions
Although participants had negative perceptions of the accelerometer, they were willing to use it for future studies, suggesting only minor design modifications may be needed. Mobile apps also should be easy to navigate and use, especially among older persons living with MS. A surprising finding was that MS mobile apps may be more appealing to younger persons living with MS who have greater disability.