Integration Guide

IMU Sensor Integration Guide: Bringing QSense into Your System

The QSense platform is designed to be integrated – into research setups, clinical systems, interactive applications and commercial products. This guide explains how to architect, configure and integrate QSense IMU sensors and platform components into your solution, from first prototype to production deployment.

It covers system architectures, communication options, synchronization strategies, data flows and typical integration patterns, so you can make the right technical choices early.

If you are building a motion-driven application or product, this guide is your starting point.

1. Integration Philosophy

QSense is built on three core integration principles:

1. Open by design – raw access, documented APIs, no black boxes
2. Scalable architecture – from single sensor to multi-device systems
3. Real-world readiness – robust timing, wireless reliability, wearable form factors

This means you can use the same platform to:

• explore ideas,
• validate concepts,
• build applications,
• and scale into commercial products.

No platform switching. No architectural dead ends.

2. Typical Integration Scenarios

Most QSense integrations fall into one of the following patterns.

a) PC / Laptop Based Integration

Architecture

IMU sensors → BLE dongle → Windows application or custom software

Typical use cases

• biomechanics research
• clinical gait analysis
• validation studies
• algorithm development

Why this setup

• maximum throughput
• stable multi-sensor performance
• easy access to tooling and visualization

b) Mobile / Tablet Based Integration

Architecture

IMU sensors → native BLE → mobile app (iOS / Android)

Typical use cases

• rehabilitation applications
• demos and pilots
• field measurements
• lightweight user interfaces

Why this setup

• no extra hardware required
• fast setup
• portable and user-friendly

c) Fully Wearable / Field-Based Integration (FieldSync)

Architecture

IMU sensors → FieldSync Hub → offline storage → post-processing

Typical use cases

• outdoor sports performance
• daily-life biomechanics
• ergonomics studies
• long-duration monitoring

Why this setup

• no laptop, tablet or phone needed
• highest robustness in the field
• continuous time synchronization

d) Embedded / OEM Integration

Architecture

Bare PCB or custom enclosure → custom firmware → your product

Typical use cases

• medical devices
• defense systems
• industrial wearables
• commercial motion products

Why this setup

• full control over hardware and firmware
• optimized form factor
• product certification pathways

3. Choosing the Right Architecture

A few guiding questions help determine the right setup:

Requirement	Recommended Approach
Lowest possible latency	Low Latency Mode + BLE dongle or native BLE
Research-grade timing	TimeSync Mode + dongle or FieldSync
Outdoor / mobile use	FieldSync Hub
High volume product	OEM PCB integration
Fast prototyping	Windows app + dongle

If you are unsure, start with the Windows + dongle setup and evolve from there.

4. Communication Options

QSense supports multiple communication strategies.

Direct BLE (Native BLE Stack)

Sensors connect directly to:

• mobile devices
• tablets
• PCs with BLE support

Pros

• no extra hardware
• simple setup

Cons

• OS-level BLE limitations
• less predictable performance for multi-sensor setups

QSense BLE Dongle

The QSense BLE dongle is engineered for:

• high throughput
• low latency
• stable multi-sensor performance

It exposes a serial interface and abstracts BLE complexity.

Use the dongle when:

• you use multiple sensors
• timing matters
• you need predictable performance
• you are building professional applications

FieldSync Hub

The FieldSync Hub is a dedicated, wearable data collection unit that:

• connects to up to 9 external QSense IMU sensors (10 IMU sensing devices in total, including the HUB itself)
• continuously synchronizes them
• records data without a PC or phone

Use FieldSync when:

• you measure outdoors
• you need maximum robustness
• you cannot rely on consumer devices

5. Time Synchronization Strategy

Accurate motion analysis depends on accurate timing.

QSense provides two synchronization modes.

TimeSync Mode – Research Grade

• continuous wireless clock synchronization
• typical inter-sensor accuracy < 60 µs
• maximum < 150 µs
• absolute timestamps

Use when:

• you do biomechanics
• you fuse with EMG / ECG / force plates
• phase relationships matter

Low Latency Mode – Interaction Optimized

• minimal end-to-end delay
• local timestamps per sensor
• drift ≤ 2 ms per minute

Use when:

• real-time feedback matters more than absolute timing
• XR / training / coaching applications

6. Data Flow & Output Strategy

QSense allows you to choose:

• what data you receive
• how often you receive it
• in which format
• how you process it

Supported Outputs

• Raw accelerometer / gyroscope / magnetometer
• Fused kinematic outputs
• 6DoF / 9DoF quaternions
• BVH skeletal motion
• Mixed mode combinations

Typical Patterns

• Research workflow: raw + fused + offline processing
• XR workflow: quaternions + low latency
• Hybrid workflow: fused for control, raw for logging

All streams share:

• synchronized timestamps
• deterministic timing behavior

7. SDK & API Integration

QSense provides APIs for:

• C# / .NET
• Unity
• Python (research)
• MATLAB (on request)
• native iOS (beta)

Through the API you can:

• configure sensors
• control streaming & logging
• manage multi-sensor setups
• access metadata & quality indicators

Ready-to-run code examples for the sensor and dongle interfaces, in C#, Python and Swift, are published in our public repository: QSense Examples on GitHub.

For API reference and examples, see SDK & APIs.

8. Multi-Sensor Performance Considerations

Wireless multi-sensor systems require attention to:

• connection interval
• sample rate
• number of sensors
• synchronization mode

As a rule of thumb:

• total throughput scales with number of sensors
• higher sample rates reduce max sensor count
• TimeSync Mode requires ≥15 ms connection interval

QSense provides guidance and tuning support to optimize your setup.

9. Calibration & Signal Quality

For reliable results:

• magnetometer calibration should be performed when environment changes
• gyroscope bias compensation is needed after large temperature shifts
• mechanical coupling to the body should be stable

QSense provides:

• calibration tooling
• quality indicators
• integration support for robust setups

10. From Prototype to Product

The same integration principles apply whether you build:

• a research setup
• a demo application
• or a commercial product

Through 2M Engineering, QSense supports:

• custom device development
• algorithm development
• firmware customization
• DFM and production readiness
• EVT / DVT / PVT phases
• regulatory guidance (CE / FCC / MDR where applicable)

This ensures that:

what works in your pilot will also work in production.

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11. Typical Pitfalls – and How QSense Addresses Them

Common Issue	QSense Approach
Timing drift	Continuous QSync synchronization
Magnetic disturbance	Mag-aware processing + raw access
Wireless instability	BLE dongle + FieldSync
Integration friction	Open APIs + examples
Prototype dead ends	OEM-ready architecture

12. Getting Started

A typical integration path looks like:

1. Start with Windows app + dongle
2. Validate sensor placement & data quality
3. Integrate via API into your application
4. Tune performance & timing
5. Scale to multi-sensor or OEM setup

We support you in each step.

Let’s Design Your Architecture Together

Every application is different. We are happy to:

• review your use case
• advise on architecture
• suggest integration patterns
• support implementation

Talk to our team about your integration approach.