One month. 1,000 people. Measurable outcomes.

A real-time warning that prevented a crash

T.N. was doing a routine task at home. She felt fine. Nothing unusual. Then her phone notified her: FatigueSense indicated she had already spent too much of her personal energy envelope for the day.

She slowed down. She did not crash.

For a clinician, this might read as a simple self-management win. For anyone living with ME/CFS or post-exertional malaise, it is a meaningful outcome. A crash can mean days to weeks of significantly worsened symptoms, cognitive impairment, and loss of functional capacity. Preventing one through timely physiological feedback is precisely the clinical goal energy pacing is designed to achieve.

T.N. had recently received an ME/CFS diagnosis following bilateral lymphoedema after a short illness. She described entering "a world with a different language: PEM, pacing, energy envelopes." FatigueSense gave that language a number, a real-time signal, and a way to act before the physiological cost was incurred.

The problem with existing digital health tools for chronic fatigue

Every fitness and activity tracking application currently on the market is built around a single behavioural model: more activity is better. Closing rings, hitting step targets, earning active minutes. These are rational design choices for the general population, where physical conditioning follows a progressive overload model and recovery is predictable.

For people with ME/CFS, long COVID, fibromyalgia, cancer-related fatigue, and rheumatoid arthritis fatigue, that model is not only unhelpful but actively harmful. Post-Exertional Malaise (PEM) is a hallmark feature of these conditions: a delayed, disproportionate worsening of symptoms triggered by physical or cognitive exertion that would be considered trivial for a healthy individual. Each person has a personal physiological threshold, and it is lower and more variable than most patients or clinicians expect. Staying within it is not deconditioning. It is the evidence-based management approach.

FatigueSense connects to the wearable a person already owns, Apple Watch, Fitbit, Garmin, Oura, Samsung Galaxy Watch, WHOOP, and others, and builds a personalised picture of that individual's energy limits. Users see a daily pacing status, real-time feedback on where they stand, and proactive alerts before their limit is reached, not after.

1,000 users in six weeks: who they are and how they found FatigueSense

The first 1,000 users reached FatigueSense organically, through peer networks within the chronic illness community. Facebook groups for ME/CFS and long COVID, Reddit communities, and direct word of mouth among patients accounted for the vast majority of installs. This distribution reflects both the tight community bonds that form around poorly understood conditions and an unmet need that existing apps had not addressed.

Users span the United States, the United Kingdom, the Netherlands, Australia, and beyond. Diagnoses include ME/CFS, long COVID, fibromyalgia, RA fatigue, and cancer-related fatigue. Wearable types range from Oura Ring to basic Fitbit trackers to Apple Watch to manual iPhone-only entry. The clinical need for evidence-based pacing tools does not correlate with socioeconomic access to premium hardware.

Findings from the first month: usability, trust, and clinical utility

The most consistent feedback from the first 1,000 users was not a feature request. It was a request to reduce cognitive load. Several users described the initial dashboard as "overwhelming." For a population that includes people managing cognitive impairment as a primary symptom, this is a meaningful finding. The information architecture of a clinical tool must account for the fact that its users may be interacting with it on their worst days.

In response, we are shipping a customisable dashboard that puts the three signals that matter most front and centre: today's pacing status, PEM risk, and the ability to log a crash. Everything else is accessible but not imposed. This is not a cosmetic update. Reducing the decision burden at the point of use is part of the clinical design.

A second consistent finding was around trust. Users who saw their pacing budget accurately reflect a day they knew had been too much reported a qualitatively different relationship with the data, one grounded in validation rather than monitoring. For a population whose symptoms are frequently dismissed or misattributed, an objective signal that confirms their lived experience appears to carry significant value beyond the functional utility of the alert.

What we are building next

A peer community for people with disabling fatigue conditions, built inside the app, where users can share what actually works without the noise of a general health forum. Structured symptom trends and pattern recognition to help users identify personal triggers over time. Better onboarding for people who are newly diagnosed and encountering the concepts of PEM and energy pacing for the first time.

None of these change the core promise: give each person a clear, personalised signal about where they stand relative to their own limits, and alert them before those limits are exceeded. For many users, that is not a wellness feature. It is a daily functional requirement.