Fatigue Investigation Using Digital Outcomes

NCT07783074 | Recruiting

• 3 other identifiers: 2024-01878108.672 IP-LSPostdoc Fellowship
• Study Type: observational
• Target: 122
• Locations: 1 country
• Sites: 6

Brief Summary

This study investigates objective methods to measure and monitor fatigue in patients with post-COVID-19 condition (long COVID) and multiple sclerosis (MS), and includes a group of healthy volunteers for comparison. Fatigue is a common and debilitating symptom of both conditions, but current assessment methods rely mainly on questionnaires, which can be limited by subjectivity and recall bias. The study uses a smartphone application (the FIDO app) together with wearable devices to continuously collect data on fatigue and its fluctuations during daily life, in order to evaluate the potential of digital, objective measures compared to standard assessments. Participation lasts approximately eight weeks and includes two in-person clinic visits along with a continuous data collection phase. At the initial visit, participants complete baseline assessments and questionnaires and are introduced to the study's digital tools. During the following weeks, participants wear two wearable devices continuously (24 hours a day) and use the FIDO app to complete short daily tasks (approximately 7 minutes every two days) and brief questionnaires (approximately 5 minutes per day). All participants collect a stool sample at home at weeks 4 and 8 for gut microbiome analysis, and complete the Fatigue Scale for Motor and Cognitive Functions at week 4. At the final study visit, participants repeat a subset of the baseline assessments, provide feedback on the digital technology used, and return the study devices.

Conditions

Multiple Sclerosis; Long Covid; Healthy

Keywords

digital biomarker; wearable devices; passive sensing; smartphone application; remote monitoring; actigraphy; heart rate variability; long COVID; Post-Acute COVID-19 Syndrome; feasibility study; compliance; adherence; fatigue monitoring; gut microbiome; post-exertional malaise; PEM; MS; FSMC; fatigue; fatigability; motor fatigue; cognitive fatigue; physical fatigue; smartwatch; ActiGraph LEAP; Apple Watch; Garmin; smartphone

Outcome Measures

Primary Outcomes (4)

• Percentage of Expected Smartwatch Wear Time Recorded Over Two Months

  Passive compliance with continuous smartwatch data collection, as a measure of feasibility of long-term fatigue monitoring. Participants wear a smartwatch continuously for two months: a Garmin smartwatch (multiple sclerosis group), an Apple Watch (post-COVID-19 condition group), or either device (healthy controls). Expected wear time is the full duration of each participant's individual enrolment (approximately 60 days), so the denominator is calculated per participant rather than as a fixed period; charging periods are not excluded, so values are not expected to reach 100%. Compliance is calculated per participant as recorded wear time divided by expected wear time, multiplied by 100. Values range from 0% to 100%, with higher values indicating greater compliance. Compliance is also compared by group, disease characteristics and demographic factors, and baseline characteristics associated with lower compliance are described.

  2 months

• Percentage of Expected Armband Activity Monitor Wear Time Recorded Over Two Months

  Passive compliance with continuous armband data collection, as a measure of feasibility of long-term fatigue monitoring. Participants wear an armband activity monitor (ActiGraph LEAP) continuously for two months. All participants wear the same device, so compliance can be compared between groups independently of device type. Expected wear time is the full duration of each participant's individual enrolment (approximately 60 days), so the denominator is calculated per participant rather than as a fixed period; charging periods are not excluded, so values are not expected to reach 100%. Compliance is calculated per participant as recorded wear time divided by expected wear time, multiplied by 100. Values range from 0% to 100%, with higher values indicating greater compliance. Compliance is also compared by group, disease characteristics and demographic factors, and baseline characteristics associated with lower compliance are described.

  2 months

• Percentage of Scheduled Study Application Questionnaires Completed Over Two Months

  Active compliance with self-reported data collection, as a measure of feasibility of long-term fatigue monitoring. Participants complete short questionnaires in the study smartphone application (FIDO app) over two months, comprising cognitive and motor fatigue visual analogue scales prompted four times daily at random times, morning and evening sleep surveys daily, and the Fatigue Severity Scale weekly in the multiple sclerosis and healthy control groups. The number scheduled follows each participant's individual enrolment (approximately 60 days). Compliance is calculated per participant as the number of questionnaires completed divided by the number scheduled, multiplied by 100. Values range from 0% to 100%, with higher values indicating greater compliance. Compliance is reported per questionnaire type, compared by group, disease characteristics and demographic factors, and baseline characteristics associated with lower compliance are described. Response latency is also evaluated.

  2 months

• Percentage of Scheduled Study Application Performance Tasks Completed Over Two Months

  Active compliance with task-based data collection, as a measure of feasibility of long-term fatigue monitoring. Participants complete two brief performance tasks in the FIDO app approximately every second day over two months: a cognitive fatigability test (cFAST) and a 30-second finger tapping task, together taking approximately seven minutes. The number scheduled follows each participant's individual enrolment (approximately 60 days). Compliance is calculated per participant as the number of sessions completed divided by the number scheduled, multiplied by 100. A session counts as completed if the participant finishes the full task protocol. Values range from 0% to 100%, with higher values indicating greater compliance. Compliance is reported per task, compared by group, disease characteristics and demographic factors, and baseline characteristics associated with lower compliance are described. Response latency is also evaluated.

  2 months

Secondary Outcomes (23)

• Discriminative Accuracy of Cognitive Fatigability Test and Finger Tapping Test Performance for Participant Group, Stratified by Fatigue Level

  2 months

• Reliability and Within-Participant Variability of Cognitive Fatigability Test and Finger Tapping Test Performance

  2 months

• Agreement Between Cognitive Fatigability Test and Finger Tapping Test Performance and Established Fatigue and Functional Assessments

  2 months

• Association Between Digital Measurements Derived From Wearable Data and the Fatigue Scale for Motor and Cognitive Functions (FSMC)

  2 months

• Discriminative Accuracy of Armband-Derived Digital Measurements for Distinguishing Patients From Healthy Controls, Stratified by Fatigue Level

  2 months

Other Outcomes (3)

• Autonomic Function and Symptoms in Participants With Multiple Sclerosis, Post-COVID-19 Condition and Healthy Controls

  Baseline and 8 weeks

• Agreement Between Blood Pressure Estimated From the Armband Activity Monitor and Cuff-Measured Blood Pressure During Clinical Autonomic Testing

  Baseline visits

• Time From Notification to Completion of Scheduled Study Application Questionnaires and Performance Tasks Over Two Months

  2 months

Study Arms (3)

Multiple Sclerosis

Participants with a clinically confirmed diagnosis of multiple sclerosis (MS). This group is monitored using two wearable devices and the FIDO smartphone application over two months. At the initial visit this cohort completes demographic questions and the following assessments: the Fatigue Scale for Motor and Cognitive Functions (FSMC), the Hospital Anxiety and Depression Scale (HADS), COMPASS-31, and the Multiple Sclerosis Impact Scale (MSIS-29). The MSIS-29 is administered to this cohort only.

Long COVID

Participants with a clinically confirmed diagnosis of post-COVID-19 condition (Long COVID). This group is monitored using two wearable devices and the FIDO smartphone application over two months. At the initial visit this cohort completes demographic questions and the following assessments: the Fatigue Scale for Motor and Cognitive Functions (FSMC), the Munich Berlin Symptom Questionnaire (MBSQ), the Bell Disability Scale, the Hospital Anxiety and Depression Scale (HADS), and COMPASS-31. The MBSQ and Bell Disability Scale are administered to this cohort only, and characterise symptom severity and functional impairment.

Healthy controls

This group is monitored using two wearable devices and the FIDO smartphone application over two months. At the initial visit this cohort completes demographic questions and the following assessments: the Fatigue Scale for Motor and Cognitive Functions (FSMC), the Hospital Anxiety and Depression Scale (HADS), and COMPASS-31.

Eligibility Criteria

• Age: 18 Years - 65 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Multiple sclerosis participants will be recruited through Bellevue Medical Group (BMG) and NeuroPraxis Zürich during routine clinical visits. External patients may also participate if they have a diagnosis from a recognized medical institution. Long COVID participants will be recruited from Klinik Lengg during routine clinical visits. External patients may also participate if they have a diagnosis from a recognized medical institution. Healthy controls will be recruited from the general community in Zurich. Recruitment across all groups will use physical and digital study flyers; the Long Covid Switzerland association will additionally support flyer distribution. Interested individuals may contact the UZH study team by email or phone to learn about study aims and eligibility; those willing and eligible will be directed to a study site.

You may qualify if:

• Confirmed diagnosis of MS (by neurologist) or Long COVID (by medical doctor).
• Smartphone ownership.
• Provide written informed consent.
• Fluent in German or English.
• Smartphone ownership.
• Provide written informed consent.
• Fluent in German or English.

You may not qualify if:

• Concomitant medication affecting fatigue or ANS such as antidepressants prescribed or adjusted 1 month before the initial visit.
• Unable to provide informed consent.
• Unwilling or unable to comply with the study protocol.
• Pregnancy or lactation.
• For controls: Diagnosis of any chronic disorders or diseases that may affect fatigue or ANS.
• For MS: Additional comorbidities that may affect fatigue or ANS such as autoimmune disease and cardiovascular disease.
• For long COVID: Additional comorbidities diagnosed prior to the first acute COVID-19 infection that may affect fatigue or ANS such as autoimmune disease and cardiovascular disease.

Sponsors & Collaborators

• Liliana Barrios: lead
• University of Zurich: collaborator
• Innosuisse - Swiss Innovation Agency: collaborator
• Insel Gruppe AG, University Hospital Bern: collaborator
• ETH Zurich (Switzerland): collaborator
• Centre Suisse d'Electronique et de Microtechnique (CSEM), Switzerland: collaborator

Study Sites (6)

Neurozentrum Basel Messeturm

Basel, Basel, 4058, Switzerland

RECRUITING

Bellevue Medical Group - Neurozentrum Sternen / Neurozentrum Bellevue

Zurich, Canton of Zurich, 8001, Switzerland

RECRUITING

University of Zurich

Zurich, Canton of Zurich, 8001, Switzerland

RECRUITING

NeuroPraxis Zürich GmbH

Zurich, Canton of Zurich, 8006, Switzerland

RECRUITING

Bellevue Medical Group - Neurozentrum Seefeld

Zurich, Canton of Zurich, 8008, Switzerland

RECRUITING

Klinik Lengg AG

Zurich, Canton of Zurich, 8008, Switzerland

RECRUITING

Related Publications (2)

• Gashi S, Oldrati P, Moebus M, Hilty M, Barrios L, Ozdemir F; PHRT Consortium; Kana V, Lutterotti A, Ratsch G, Holz C. Modeling multiple sclerosis using mobile and wearable sensor data. NPJ Digit Med. 2024 Mar 11;7(1):64. doi: 10.1038/s41746-024-01025-8.

  PMID: 38467710 BACKGROUND

• Barrios L, Amon R, Oldrati P, Hilty M, Holz C, Lutterotti A. Cognitive fatigability assessment test (cFAST): Development of a new instrument to assess cognitive fatigability and pilot study on its association to perceived fatigue in multiple sclerosis. Digit Health. 2022 Aug 25;8:20552076221117740. doi: 10.1177/20552076221117740. eCollection 2022 Jan-Dec.

  PMID: 36046638 BACKGROUND

MeSH Terms

Conditions

Multiple Sclerosis; Post-Acute COVID-19 Syndrome; Patient Compliance; Fatigue

Condition Hierarchy (Ancestors)

Demyelinating Autoimmune Diseases, CNS; Autoimmune Diseases of the Nervous System; Nervous System Diseases; Demyelinating Diseases; Autoimmune Diseases; Immune System Diseases; COVID-19; Pneumonia, Viral; Pneumonia; Respiratory Tract Infections; Infections; Virus Diseases; Coronavirus Infections; Coronaviridae Infections; Nidovirales Infections; RNA Virus Infections; Lung Diseases; Respiratory Tract Diseases; Post-Infectious Disorders; Chronic Disease; Disease Attributes; Pathologic Processes; Pathological Conditions, Signs and Symptoms; Patient Acceptance of Health Care; Treatment Adherence and Compliance; Health Behavior; Behavior; Signs and Symptoms

Central Study Contacts

Liliana Barrios, Dr. sc. ETH Zürich

CONTACT

+41774141174; fido@dsi.uzh.ch

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR INVESTIGATOR
• PI Title: Principal Investigator

Study Record Dates

• First Submitted: August 14, 2026
• First Posted: August 24, 2026
• Study Start: May 26, 2026
• Primary Completion (Estimated): May 1, 2028
• Study Completion (Estimated): May 1, 2028
• Last Updated: August 24, 2026

Record last verified: 2026-08

Locations

CH (6)