A clear question.
Evidence that matters.
Synseer invites research teams to explore ear-based sensing, listening or pediatric feasibility questions. A collaboration starts with a defined population, endpoints, reference method and consent plan.
Ear-based sensing feasibility study
An adult feasibility study compares a predefined ear-based observation with a reference method under specified wear conditions.
- What your team brings
- Lead study design, participant oversight, reference measurements, and applicable approvals.
- What Synseer brings
- Describe the prototype configuration and help document collection, fit, and signal-quality criteria.
- What we review
- A feasibility review covering usable recordings, comparison with the reference, and limits by condition.
- The decision together
- Decide whether a revised protocol or a broader validation study is warranted.
Illustrative project · Teams agree on scope, readiness, and criteria before starting.
How We Test Ear-Based Sensing
52 seconds
Read the film transcript
What makes a signal from the ear useful? Fit and movement can change what we pick up.
Synseer uses a unique combination of four forms of sound to gather critical biometric information. Infrasonic sound, ultrasonic sound, otoacoustic emissions, or OAE, and ultra-high-frequency sound, or UHF.
MindMics is our partner in infrasonic sensing. Its published research compared heart rate and beat-to-beat timing with ECG.
Synseer’s integrated products require their own evidence. We define who takes part, what to compare against, and when a signal is too uncertain to use.
Explore the research with Synseer.
Define the question before the display.
Specify the population, conditions, outcome and reference method. A longitudinal study could test whether several signals aligned in time and compared with a personal baseline improve prediction of a defined outcome.
Plan for quality and uncertainty.
Fit, movement, completeness and unusable observations should be considered in the evidence plan. A study needs a way to recognize both useful data and its limits.
Keep governance in the work.
Consent, access, protocol requirements and reporting belong in the collaboration from the start. Study status and findings should be communicated only at the level the evidence supports.