A wearable + app system that translates sweat biomarkers into plain-language guidance — before, during, and after exercise.
Athletes and casual exercisers alike make every training decision — how hard to push, when to stop, how to recover — based entirely on subjective feeling. There is no real-time data informing these choices.
Existing wearables measure physiological signals: heart rate, steps, SpO₂. What they miss is the biochemical layer — what is actually happening inside the body at a metabolic level during exertion.
Sweat encodes that layer. The question SOMA asks: can we translate it into guidance a non-expert can act on?
Active but uninformed. The missing link isn't motivation or access to equipment — it's real-time feedback from the body itself.
— Core design problem, synthesised from user research + market analysisSweat is one of the most studied biofluids in wearable sensor research. It is non-invasive, continuously available during exercise, and contains multiple signals that correlate with metabolic state.
Honest design constraint: Sweat lactate as a proxy for blood lactate remains scientifically debated — correlations vary by sweat rate, body site, and individual. Cortisol detection is promising but consumer validation is limited. SOMA's framing is intentionally careful: it presents signals as guidance inputs, not clinical diagnostics. This distinction matters and should be visible in the product's voice.
The product logic maps to two distinct physiological questions that athletes face but currently can't answer with data.
n=100 questionnaire to map injury patterns, plus three in-depth interviews across a spectrum of exercise engagement — from sporadic beginner to data-driven enthusiast.
"I exercise freely but have no regularity — hard to stay consistent."
Relies entirely on feeling to gauge effort. No awareness of concepts like warm-up or recovery. When pain occurs, default response is to ignore it or stop without understanding why. Needs guidance that doesn't require prior sports knowledge.
"I need data to tell me what my body actually needs."
Trains consistently and tracks data, but has hit a plateau. Current devices give heart rate and steps — not the metabolic insight she needs to break through. Frustrated by conflicting advice online. Wants expert-level feedback without a sports scientist.
"Pain occurred during yoga — I just ignored it."
Classic body blindness pattern: discomfort without context leads to dismissal. No feedback loop between pain signal and behaviour change.
"Good habits = zero injuries so far."
Structured warm-up and cool-down replaces the need for real-time data. Demonstrates that behaviour, not just technology, drives injury prevention — SOMA's design must reinforce habit formation, not just surface numbers.
"Recovery took very long — still have sequelae."
Insufficient warm-up led to ankle and knee injuries with lasting effects. Represents the highest-stakes case: overload that wasn't detected until after the injury occurred. Exactly the scenario SOMA's in-session alert is designed to prevent.
Sweat biomarkers are meaningless to non-experts. Every sensor reading must be translated into an action the user can take. "Your lactate is rising fast" becomes "Reduce your pace."
The system earns its place by being useful at critical moments, not by collecting data continuously. Alerts should feel like a knowledgeable training partner — not an alarm system.
The science of sweat biomarkers is still maturing. SOMA's UI language reflects this — signals are framed as inputs for decision-making, not clinical facts. This trust boundary is a design choice, not a disclaimer.
Each screen owns a specific moment in the Before / During / After structure. No screen does more than one job.
The key insight from competitive analysis: Apple Watch and fitness trackers measure physiological signals. SOMA measures biochemical ones. These are fundamentally different layers of information — not competing features.
| Product | HR / HRV | Sweat lactate | Electrolytes | Cortisol | Real-time guidance | Plain language output |
|---|---|---|---|---|---|---|
| Apple Watch Ultra | ✓ | — | — | — | Partial | Partial |
| Garmin Fenix | ✓ | — | — | — | Partial | — |
| Whoop 4.0 | ✓ | — | — | — | ✓ | ✓ |
| Smart clothing (Hexoskin) | ✓ | — | — | — | — | — |
| SOMA SweatSense | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
Upper-arm band with microfluidic biosensor array detecting sweat lactate, sodium, cortisol, and pH in real time. Designed for wearability during high-intensity exercise.
Plain-language guidance across Before / During / After — readiness score, live overload alerts, and a data-driven recovery plan. Science translated into decisions a non-expert can make.
Addresses sweat biomarker detection and fatigue prevention together in a single consumer product — bridging the gap between sports science research and accessible health technology.