Fewer prototypes, earlier answers
See how signals shift with placement, posture and movement in virtual experiments first. Prototypes and development time come down together.
Fields Biosignal AI
Biosignal AI
Biosignal AI, from sensor to bedside
From validating wearable-sensor designs to signal processing, anomaly detection and real-time monitoring at hospital scale. We turn ECG, PPG and respiration signals into AI that works in real products and real hospitals.
Fewer prototypes, signals you can trust
Less noise, more usable signal
Signal-quality checks, motion-artifact classification and multi-channel estimation keep the segments you can actually use.
Detection that runs in the product
Anomaly-detection algorithms for ECG and other biosignals, built for the compute budget of the device they ship in.
From one patient to thousands
Wearable-patch signals from thousands of patients, collected in real time, with alarms, location, records and EMR integration in one system.
From signal to system
| ECG | Waveform synthesis and acquisition, heart-rate extraction, anomaly detection, ECG-derived respiration (EDR) |
|---|---|
| PPG | Green, red and infrared wavelengths; wrist, finger and ring sensors; heart-rate and SpO₂ reference values |
| Respiration | Capacitance patches, accelerometer respiration, multi-channel respiratory-rate estimation |
| Other signals | EEG · EMG · temperature · glucose · 3-axis acceleration |
| Signal processing | DSP filtering, signal-quality checks, motion-artifact classification, optimisation for constrained hardware |
| Real-time transport | Per-gateway transport, 200 ms frames, CRC integrity checks and retransmission |
| Integration | EMR integration via FHIR, HL7 v2 and more; CSV and JSON export |
From problem to handover, in four steps
- 1Define
Agree the measurement goal, sensor sites, required signals and validation criteria up front.
- 2Simulate and build
Review placement and conditions with synthetic signals, then build the processing and detection algorithms.
- 3Integrate and load-test
Connect gateways, servers and EMRs, and load-test at operating scale.
- 4Validate and hand over
Validate on your data, then hand it over for your own staff to run.
Frequently asked questions
Can we start without measured data?
Yes. Synthetic signals in a virtual test environment let you review sensor placement and measurement conditions first, and narrow the real data you need to collect.
Can it work with our existing sensors or gateways?
Your equipment and systems stay as they are; we build on top of them. Transport format and channel layout are agreed at kickoff.
What about medical-device regulatory approval?
Clinical use requires medical-device regulatory approval after deployment. The solution becomes the customer’s own product, so the approval is obtained directly in the customer’s own name.
Who runs it once development is done?
You do. Code and documentation are handed over so your own staff can run it, with admin tooling where needed.
Talk to us
Tell us the signal and the goal.