Key Challenges & Solutions
Huge Volumes of Continuous, High-Frequency Sensor Data
ECG, EEG, and IMU sensors produce dense waveforms that must be stored for long periods and analyzed without distortion. This quickly overwhelms storage in wearables, gateways, and cloud systems.
How Byte2Bit solves it:
- MedCodec achieves 3×–7× lossless compression on biomedical signals while preserving clinically meaningful features.
- Reduced storage means longer monitoring periods, larger datasets for diagnostics, and more efficient remote-patient monitoring pipelines.
Limited Bandwidth for Real-Time Medical IoT Devices
Wearables and portable medical sensors often operate over BLE, WiFi, or narrowband networks, all of which struggle to transmit full-resolution biomedical streams in real time.
How Byte2Bit solves it:
- MedCodec cuts network load by 3×–7×, ensuring stable real-time transmission of ECG/EEG/IMU data.
- Low latency and low overhead make it ideal for telehealth, home monitoring, and ambulatory medical devices.
Strict CPU & Memory Constraints on Wearables and Edge Devices
Medical IoT is dominated by microcontroller platforms (ESP32, Cortex-M series). These devices cannot run heavy compression algorithms without draining battery or degrading performance.
How Byte2Bit solves it:
- MedCodec uses minimal CPU and memory, enabling continuous on-device compression even on lightweight MCUs.
- MedCodec achieves 20–50 MB/s throughput on Cortex-M and ESP32-class processors, providing real-time compression with negligible power impact.
- Together, they extend battery life and keep edge processing smooth and reliable.
Use Cases
Wearables & Medical IoT
Ideal for wearables, bedside sensors, and remote patient monitoring nodes.
- Continuous on-device compression
- Extended battery life
- Real-time signal transmission
Telehealth & Home Monitoring
Enable stable real-time transmission for telehealth applications.
- Low-latency data streaming
- BLE and WiFi optimization
- Ambulatory device support
Clinical Research
Support large-scale research studies with efficient data storage.
- Longer monitoring periods
- Larger diagnostic datasets
- Efficient remote-patient monitoring
Benefits
Compression Ratio
3X–7X
Lossless Compression
Throughput
20–50 MB/s
On Embedded Cores
Network Load
3X–7X
Reduction In Transmission
Accuracy
100%
Clinically Safe