MEDTRAC™ – Wearable Sensor
This 4Trac wearable integrates four medical-grade sensors (HRV, movement, GSR, and biophoton) to deliver multiple concurrent signal streams that can be triangulated to generate both real-time and longitudinal data across the MEDTRAC Health, Wellness, Sports, Performance, Longevity, and Clinical Decision platforms.
This design is the result of MEDTRAC’s research into existing health wearables, which were found to lack the real-time data-streaming resolution and granularity required for MEDTRAC’s precision health platform. It also incorporates our research into UVA and UVB spectral bands to assess rapid autonomic nervous system response variability.
If the design goals are achieved, it will allow us to capture sufficient data to perform a remote wellness test on clients and facilitate continuous live health monitoring.
This early design is based upon integrating existing medical grade sensor technology to allow it to be brought to market without complex and costly 1-2 year medical device testing. By designating it as a research tool, we can use in the clinical and with research clients for monitoring during testing & treatment.
MEDTRAC Remote Scan Data Capture Sensor
(Research-Stage, Multi-Modal Wearable for Closed-Loop Biofeedback Analysis)
1. What This Product Is (in one sentence)
A research-stage wearable biofeedback device that combines GSR, optoelectronic light sensing (UVA/UVB), and inertial/HRV data to capture real-time physiological response during frequency-based interrogation, producing synchronized, multi-channel data for longitudinal health, performance, and illness analysis.
2. Why This Device Exists
MEDTRAC Remote Scan Data Capture Sensor
A Research-Stage Multi-Modal Wearable for Closed-Loop Biofeedback Analysis
Product Summary
The MEDTRAC Remote Scan Data Capture Sensor is a research-stage wearable designed to measure how the human body responds in real time to controlled stimuli. It combines galvanic skin response (GSR), optoelectronic light sensing (UVA/UVB), and movement and heart-rate variability (HRV) context into a single, compact forearm-worn device.
Rather than measuring static health metrics, the device focuses on physiological response — how the nervous system, metabolic signalling, and recovery systems behave moment by moment. This makes it suitable for longevity optimisation, general health analysis, and complex chronic conditions, without diagnosing or prescribing treatment.
The device is currently positioned as a research, wellness, and performance analysis tool, with a clear pathway toward a future production-ready, licensable platform.
Why This Device Exists
Most consumer wearables measure state: heart rate, steps, sleep stages, or calories. These metrics are useful, but they describe what the body looks like at rest or over time.
Most clinical biofeedback tools, on the other hand, attempt to measure response — but often rely on subjective techniques, manual interpretation, or equipment that does not scale beyond a clinic setting.
The MEDTRAC Remote Scan Sensor is designed to sit between these two worlds. It is objective, repeatable, response-aware, and built specifically for closed-loop analysis. Instead of asking “What is the body doing?”, it asks a more important question:
“How does the body respond, right now, to a defined stimulus — and how does that response change over time?”
Use Cases – Who can use the product ?
Originally designed to help automate In Clinic realtime test biofeedback, the device may also be suitable for the following groups subject to testing & validation.
- Wellness & Longevity
- Performance Training & Sports
- High Stress-Risk Industries (Nuclear power stations, emergency doctor)
- Sports Team Monitoring – Training or live (where permitted)
- Medical Health Monitoring (as a regulated device)
Core Design Philosophy: Triangulation
At the heart of the device is a simple principle: no single signal is trusted on its own. Physiological systems are complex, noisy, and context-dependent. Reliable insight only emerges when multiple independent signals move together.
To achieve this, the device captures five synchronised data streams, each measuring a different aspect of human physiology.
Autonomic Response: Galvanic Skin Response (GSR)
GSR provides a fast, direct window into the autonomic nervous system. By measuring changes in skin conductance and resistance, the device captures how quickly the body reacts, the direction of that reaction, and how efficiently it recovers.
In MEDTRAC’s approach, GSR is not used as a generic “stress score.” Instead, it functions as a reaction detector during frequency exposure, biofeedback interrogation, and closed-loop testing. This matters because GSR reacts within seconds, whereas slower metrics such as HRV can take minutes to meaningfully shift.
This immediacy makes GSR essential for understanding cause-and-effect rather than correlation.
Metabolic and Cellular Proxy: Optoelectronic Light Sensing
Alongside GSR, the device uses UVA, UVB, and photonic light sensors to detect subtle changes in light emission and reflection at the skin surface. These signals act as a non-contact proxy for metabolic and cellular activity.
Crucially, optical sensing is a completely independent physical modality from GSR. One measures electrical resistance; the other measures photons. When both signals shift together during a stimulus, confidence in the result increases. When they diverge, the system flags uncertainty rather than forcing an interpretation.
This multi-physics approach dramatically reduces false positives compared to single-vector systems and helps distinguish genuine physiological response from artefact or noise.
Context and Readiness: Movement and HRV
The third data stream provides background context rather than real-time interrogation. Using an IMU and HRV-capable sensor (Movesense-class or equivalent), the device tracks movement, posture, recovery state, and autonomic balance over time.
This channel is not used to decide responses in real time. Instead, it establishes safety boundaries, readiness, and longitudinal baselines. In simple terms, it helps answer whether the body is stable enough to respond meaningfully and whether observed changes are likely genuine or confounded by motion, fatigue, or stress.
Physical Product Concept
The device is designed as a compact forearm-worn module, approximately the size of a Movesense sensor plus around 50% additional volume. It mounts on a soft Velcro strap, ensuring consistent placement and pressure without discomfort.
Skin contact is required for GSR electrodes, while a small optical window enables light sensing. Movement and HRV data can be captured via an embedded IMU or paired sensor, depending on deployment.
From the outset, the design is modular. Sensor blocks are replaceable, and all components are sourced from commercially available, already-certified sensor technologies. This is a deliberate choice to accelerate development, reduce risk, and keep regulatory positioning clear.
Regulatory Positioning and Intent
The MEDTRAC Remote Scan Sensor is not a diagnostic medical device. It does not make medical claims, prescribe treatment, or replace clinical judgement. It is designed as a data capture and biofeedback measurement tool, providing structured inputs into analysis workflows rather than outputs or decisions.
Importantly, assembling pre-approved sensor components does not automatically make the device a Class II or IIa medical device, particularly when no diagnosis or treatment is provided and outputs are framed as signals, trends, and responses. This positioning mirrors how fitness trackers, HRV monitors, and research-grade biosensors are commonly deployed today.
A future production version could be CE-marked as a wellness or research device, or follow a controlled medical pathway if required. Nothing in the current design forces that decision prematurely.
How the Device Fits into the MEDTRAC Ecosystem
In practical terms, the wearable quietly measures how the body reacts using skin response, light signals, movement, and heart rhythm. At the same time, the MEDTRAC platform introduces controlled frequency-based stimuli for analysis or biofeedback.
The system then observes what happens next. Does the nervous system react? Does metabolic signalling shift? Does the body recover smoothly or show signs of overload? These reactions are captured in real time — not guessed, not interpreted emotionally, just measured.
Over days and weeks, MEDTRAC compares responses across time, across frequencies, and across phases of stress and recovery. The result is a profile of how the body behaves, not just how it feels. This approach works for longevity optimisation, general health, and complex multi-system illness, without diagnosing disease.
Closed-Loop Logic at a High Level
The logic is intentionally simple. Sensors capture response. MEDTRAC evaluates signal changes. Frequencies are sequenced or adjusted. Sensors confirm response or overload. The loop repeats.
The system does not assume a frequency is good or bad. It asks a single grounding question: what did the body actually do?
Why This Matters: A Structural Breakthrough
This approach represents a genuine structural shift rather than incremental improvement. Most systems rely on one signal and one interpretation method. MEDTRAC combines electrical (GSR), optical (light), and mechanical/autonomic (IMU and HRV) signals simultaneously.
Instead of predicting what should work, the system measures what did work — in that body, at that moment. This is essential for longevity optimisation, chronic illness, and complex cases where averages and population models fail.
Because the sensors are wearable, the logic deterministic, and the analysis longitudinal, the system scales beyond the clinic. It can operate at home, in research cohorts, and across populations without clinician presence at every step. The clean separation between data capture, analysis, stimulus, and human judgement is exactly the structure regulators prefer.
Why the Forearm Was Chosen
The forearm is not an arbitrary choice. It represents the best overall compromise between signal quality, practicality, and compliance.
For GSR, the forearm provides reliable sweat gland activity without the excessive noise seen in fingers or the low responsiveness of the upper arm. For optical sensing, the skin is thin, relatively hair-free, and offers consistent light absorption characteristics. For movement and HRV context, the forearm captures stillness and posture cleanly without constant fine-motor interference.
Mechanically, the forearm offers a flat, stable surface with controlled strap tension and minimal joint flexion, enabling repeatable placement across sessions. From a user perspective, it is non-invasive, discreet, comfortable under clothing, and easy to apply without training. From a regulatory standpoint, it avoids high-risk anatomical areas such as the head, chest, or neck and aligns with established wellness and research instrumentation norms.
The forearm does not win every category outright — but it wins overall, which is what matters for a scalable platform.
Product Status Statement
The MEDTRAC Remote Scan Data Capture Sensor is a research-stage wearable designed to collect synchronised biofeedback signals during controlled frequency exposure. It is intended for investigational, wellness, and performance analysis and does not provide diagnosis or treatment. The system is built using commercially available sensor technologies and is being developed with a view toward a future licensable, production-ready platform.
Product History
Across ~18 months of discussion, GSR evolved as follows:
- 2025 H1: Conceptual replacement for subjective response tools
- 2025 H2: Core active input to Grade Scan logic
- 2026 Jan: Physical device, no longer theoretical
- Today:
- GSR + Light = active interrogation stack
- HRV = passive longitudinal context
- Zyto = optional comparative tool
Interactive Agile Planning Structure
This is an internal progress + confidence view that answers:
An example plan that will be fine tuned.
Where are we actually now
How close are we to something usable
What is blocking progress vs just pending
12. Progress Plan and Timeline (Internal)
This section tracks where the 4Trac wearable actually is, how close it is to meaningful use, and how work is staged to reduce risk and wasted effort.
The plan is intentionally iterative and evidence-driven, not a fixed waterfall timeline. Dates reflect target windows, not commitments.
12.1 Current Overall Status (Snapshot)
- Concept maturity: High
- Sensor selection: In progress
- Physical prototype: Not yet assembled
- Data capture: Not yet live
- Platform ingestion: Not yet live
- Clinical shadow testing: Planned
At present, 4Trac is conceptually complete but physically pre-prototype.
12.2 Phase 1 – Sensor Stack Confirmation
Target window: Feb–Mar 2026
Goal: Lock the minimum viable sensor stack before building hardware
Objectives
- Confirm Movesense HRV sensor as baseline HRV and IMU source
- Select GSR sensor suitable for forearm placement and continuous wear
- Finalise optical sensor candidates for UVA UVB and photonic response
- Validate availability of developer kits and documentation
Definition of Done
- All sensors physically available or ordered
- Electrical and software interfaces understood
- Known limitations documented
Current status
- Movesense HRV identified
- GSR selection in progress
- Optical sensors under evaluation
12.3 Phase 2 – Edge Data Capture Prototype
Target window: Mar–Apr 2026
Goal: Prove that data can be captured reliably on-device and on mobile
Objectives
- Capture raw HRV and movement data to mobile
- Capture raw GSR data to mobile
- Timestamp and synchronise streams
- Store data locally and export for analysis
Important constraint
At this stage, no platform logic is required. This phase is about signal fidelity, not interpretation.
Definition of Done
- Stable mobile data capture for at least one sensor
- Raw data visible and reviewable
- Basic session start stop working
12.4 Phase 3 – Multi-Sensor Synchronisation
Target window: Apr–May 2026
Goal: Validate triangulation is technically feasible
Objectives
- Capture HRV movement and GSR simultaneously
- Align timestamps across streams
- Identify noise and motion artefacts
- Test forearm placement repeatability
Key question this phase answers
Can we reliably tell that two independent signals reacted at the same time?
Definition of Done
- Multi-channel datasets captured
- Clear understanding of synchronisation error
- Decision on whether optical sensing is added in next iteration or deferred
12.5 Phase 4 – Platform Ingestion and Correlation
Target window: May–Jun 2026
Goal: Close the loop between device and MEDTRAC platform
At this stage we will have built a Clinical prototype as a larger device that simulates the Mobile phone and Senor device as one unit, as an optional for factor more suitable for clinics and hospitals. A larger device is much lower cost and easier to “prototype” before we need to miniaturise components.
Objectives
- Ingest sensor data into a POC backend
- Correlate sensor response with Grade Scan data
- Visualise response timelines
- Compare sessions longitudinally
Important
This phase is still analysis-only. No automated decisions.
Definition of Done
- Sensor data visible alongside Grade Scan outputs
- Manual correlation possible
- Gaps and inconsistencies identified
12.6 Phase 5 – Shadow Mode Clinic Testing
Target window: Jun–Aug 2026
Goal: Observe behaviour in real-world conditions without clinical dependence
Objectives
- Run 4Trac alongside existing clinic workflows
- Collect HRV and GSR during sessions
- Compare perceived response vs measured response
- Identify usability issues
Definition of Done
- Multiple real sessions captured
- Qualitative and quantitative feedback logged
- Clear list of design changes required
12.7 Phase 6 – Iteration and MVP Boundary
Target window: Aug–Sep 2026
Goal: Decide what constitutes a first usable MVP
Questions answered
- Which sensors are essential vs optional
- What signal quality is good enough
- What data is actually useful to clinicians and analysts
- What can be deferred safely
Output
- MVP definition
- Updated hardware and software backlog
- Decision on next investment step
12.8 Agile Working Model (Proposed)
Rather than treating this as a linear build, 4Trac development follows short evidence loops.
Sprint unit
- 2–3 weeks
- One clear question per sprint
Examples
- Can GSR stay stable on forearm during motion
- Does HRV add meaningful context in real sessions
- Does optical sensing add signal or noise
Artefacts
- Raw datasets
- Short findings summary
- Go no-go decision
This keeps progress measurable even when hardware is not yet “finished”.
12.9 Confidence Indicators (Internal)
Use these to answer “how close are we?”
- When we can capture one clean signal → early technical validation
- When two signals align reliably → triangulation proven
- When platform correlation works → system viability
- When clinic shadow tests feel useful → product relevance
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