Traditional consumer wearables rely on optical photoplethysmography (PPG). They estimate pulses... but completely miss the underlying electrophysiology.
⚠️ Standard Smartwatches (PPG)
25 Hz Optical Absorption
Sampling Rate:25 Hz (Low Fidelity)
Motion Resilience:Severe Optical Artifacts
Microvolt P-Q-R-S-T:Unavailable
⚡ BeatioPulse™ Innovation
500 Hz True Biopotentials
Biomedical Precision:24-Bit TI ADS1293 AFE
Sampling Velocity:500 Hz Continuous
CMRR Common Noise Rejection:105 dB Medical Grade
Stage 1: Edge Acquisition
It Starts Right at the Skin
An ultra-thin medical LSR silicone chest patch captures real-time electrical microvolts with laboratory biopotential fidelity.
Ultra-Thin Ergonomic Biopotential Patch
Designed for uninterrupted 14-day wear. Shunts motion noise, resists swimming and high-intensity workouts, and encodes microvolt biopotentials directly into BLE 5.3 binary frames.
500 Hz
Continuous biopotential sampling
24-Bit
Analog Front-End resolution
1.2 µV
Ultra-low peak-to-peak noise floor
BLE 5.3
Auto-negotiated 247-byte MTU
Stage 2: Gateway Relay Architecture
Zero Cellular Cost. 48-Hour Resilience.
Instead of draining battery on expensive cellular hardware, the patch offloads encrypted telemetry to the phone daemon—holding up to 48 hours of data offline.
Intelligent Smartphone Gateway
Runs quietly as a native iOS background central and Android foreground service. When you step into a subway tunnel or dead zone, the encrypted SQLite ring buffer guarantees zero dropped heartbeats.
🔒 Encrypted SQLite Ring Buffer48h Capacity
Buffered: 86,400,000 SamplesPacket Drop Rate: 0.000%
Apple HealthKit
Synchronized sleep & workouts
Google Connect
Multi-modal context enrichment
● Background Daemon ActiveBLE 5.3 CONNECTED
Live Ingestion Stream
500.0 pkt/s
TLS 1.3 WebSocket Framing
Stage 3: Distributed Ingestion
High-Throughput Cloud Event Highway
Binary Protocol Buffers stream through TLS 1.3 WebSockets into Apache Kafka 3.6 with Redis monotonic deduplication.
📡
Cloud Gateway
TLS 1.3 Protobuf Ingestion
⚡
Apache Kafka 3.6
Partitioned by account_id
🛡️
Redis 7 Dedup
Idempotent Monotonic State
📊
TimescaleDB
90% Compressed Waveforms
Sub-Second Latency
Total edge-to-cloud transit under 315 ms, enabling real-time waveform scrubbing anywhere.
Strict Sample Ordering
Kafka FIFO partitioning guarantees zero sample inversion during mobile tower handoffs.
7-Year Immutable Lake
AWS S3 Iceberg WORM storage preserves uncompressed raw waveforms for clinical longevity.
Stage 4: The Innovation Core
Dynamic Personal Baseline AI
Instead of rigid population tables, BeatioPulse computes a 14-day rolling mathematical model of your unique cardiovascular rhythm.
🏃 Scenario A: Outdoor Sprint
Context: HIIT Workout
135 BPM
User context confirmed via Apple HealthKit. Heart rate elevation directly matches physical exertion curves and metabolic demand.
✅
Normal Cardiovascular Exertion Expected circadian activation. Zero alert fatigue.
🚨 Scenario B: Deep Sleep (3:14 AM)
Context: Resting Circadian Dip
135 BPM
Exact same 135 BPM detected during restorative REM/Deep sleep. Significant deviation (>3σ) from personal 14-day resting baseline.