SiFi Band

The premier multi-channel EMG armband for advanced biomechanics and human-computer
interaction research.

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SiFi Band
Multi-Channel EMG band (8-channels)
Integrated Multi-Sensor Suite
Real-Time Data Streaming
Open, Cloud-Free Data Access

Product overview

The SiFi Band is the definitive tool for advanced biomechanics and multi-site muscle activity analysis. Its eight-channel, high-fidelity EMG system is engineered specifically for complex gesture recognition and rehabilitation applications where a complete neuromuscular picture is essential.

Integrated with a full suite of physiological sensors and designed for high-throughput, real-time data streaming, it provides an unparalleled, synchronized view of human movement and intent. Like all SiFi Labs hardware, it provides complete, unrestricted local access to your raw data, giving you the power to pioneer the next generation of HCI.

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Detailed specifications

Sensors

EMG (Electromyography)
8 channels of high-fidelity muscle activity at 1500 Hz
ECG (Electrocardiography)
Research-grade electrical heart activity at 500 Hz
EDA (Electrodermal Activity)
Measures autonomic arousal via sweat gland activity at 50 Hz
PPG (Photoplethysmography)
Multi-wavelength (Blue, Green, Red, InfraRed) for pulse and SpO2 derivation at 100 Hz
IMU (Inertial Measurement Unit)
6-axis accelerometer & gyroscope for precise motion tracking at 100 Hz
Skin Temperature
Continuous monitoring of peripheral skin temperature at 1 Hz

Hardware & Performance

Battery
300mAh Li-Po providing up to 16 hours of continuous data acquisition
Feedback
Independently controlled dual LEDs and a vibrotactile motor
Dimensions
20.4cm x 4.6cm x 1.3cm
Weight
62g
Connectivity
Bluetooth Low Energy (BLE) optimized for high-throughput, multi-channel streaming

See the Data for Yourself

Download sample data

Resources

SiFiBand Description
SiFiBand Description EnglishDownload
SiFiBand EMG Examples
SiFiBand_DataSampleDownload

Partners & Collaborators

Open access to raw signals gave us full control over processing and analysis, while ensuring all data remains local, greatly facilitating GDPR compliance and ethical approval processes.

Prof. Alexander Refsum Jensenius

Director of MishMash, the Centre for AI & Creativity in Norway, University of Oslo

EMG-based musical instrument research involving human movement and sound interaction.
SiFi’s platform enabled new insights into how rhythm, movement, and autonomic signals interac, thanks to seamless multi-sensor synchronization.

Assoc. Prof. Valentin BĂ©gel

Support for signal, multi-modal exploration, Université Paris-Cité

Cognitive-motor research using multimodal sensor
With the BioPoint we can test novel trauma-treatment paradigms, made even more useful by the team’s ability to customize the device to our needs.

Dr. Nina Mørkved

Head of Research and Innovation at Helgeland Hospital, Associate Professor at the Department of Psychology The Arctic University of Norway

Psychosis and trauma focused therapy.
We needed a device that could adapt to our research needs, not the other way around. SiFi Labs is building us a custom solution to do exactly that.

Dr. Hongchul Sohn

Research Assistant Professor, Physical Therapy and Human Movement Sciences, Northwestern University

Pediatric rehabilitation; needed custom sensor setup
For the first time, SiFi Labs’ devices let us study the autonomic responses of people with spinal cord injuries, both above and below the injury site – in a real-world rehabilitation setting.

Dr. Thomas Glott

Specialist in Physical and Rehabilitation Medicine, Sunnaas Rehabilitation Hospital

Early clinical exploration of physiological monitoring in neurorehabilitation.