suitX by Ottobock: What's in the Hardware – and What Does Airgo XP Actually Measure?

You are planning to introduce exoskeletons at your facility and want to understand what the bundled analytics solution actually does. Fair question. The answer depends on the measurement principle – and that is rarely spelled out in the brochure.

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What Does the suitX System Promise?

Back disorders are among the leading causes of long-term absence in logistics, manufacturing, and assembly. That is not a new finding – what is new is that systems now exist that can both offload and measure simultaneously. suitX by Ottobock is one of the best-known in the DACH region. Buy the exoskeleton, book the analytics, pull the data, derive measures. That sounds straightforward.

Three products form the suitX back portfolio. Two offload. One analyses. Understanding exactly what the analytics tool measures – and what it physically cannot measure – is worth knowing before you commit.

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The Hardware in Detail: IX BACK AIR, IX BACK VOLTON and Airgo XP

IX BACK AIR is passive. No electronics, no battery. A carbon-spring structure supports the torso during forward bending and returns energy on the way back up. Schmalz et al. (2022) studied the predecessor model Paexo Back in a lab setting – repetitive lifting, 10 kg, n=10: compression forces at L4/L5 dropped by 21 %, at L5/S1 by 20 %. Back muscle activity fell by 18 %. Solid numbers, with the usual lab caveats.

IX BACK VOLTON is the active model. Electric motor, battery, more weight. Designed for variable loads and frequent changes of direction – the classic intralogistics scenario.

Airgo XP is the analytics tool. And this is where it gets interesting: it is not a dedicated sensor. It is a Samsung Galaxy XCover 7 – a rugged Android smartphone. suitX states this directly on its product page: "Introducing the AIRGO XP user device: the robust, high-quality, and enduring Samsung Xcover 7."

The device is worn on the body. The suitX app runs on it, and data is anonymized before reaching the manager dashboard.

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How Airgo XP Actually Measures

The smartphone contains an integrated IMU – accelerometer and gyroscope. No specialty chip; the same sensor principle found in every modern phone. The accelerometer measures gravitational acceleration and derives the tilt angle from it. The gyroscope captures angular velocities. Together: an estimate of torso orientation.

The app converts this into an Ergo Score and counts bending events (Bends), steps, calories, and weights lifted. The manager dashboard shows how load is distributed across workstations. Three activity states are distinguished: Idle, Travel, and Pick & Pack.

For the question "how often and how long is employee A in a strongly bent posture per shift?" – this works well. The system reliably detects tilt angles of the trunk segment.

What it does not see: where in the spine the bending originates. More on that in a moment.

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IMU vs. Geometry Measurement: The Key Difference

Picture someone bent 30° forward. That posture can come from:

• bending at the hip with a straight spine
• pronounced thoracic kyphosis
• lumbar hyperflexion with the lordosis flattened out
• some combination of all three

A single IMU on the back sees only the total angle. It cannot determine which spinal segments are involved. Lordosis, segmental torsion, lateral flexion at specific levels – these are geometric properties. A single sensor provides no geometry.

Research puts numbers on this. González-Alonso et al. (2026) validated an IMU system for RULA ergonomics assessments in an automotive factory: RMSE below 10° for elbow joints, below 12° for shoulder joints, compared to a reference system. Cross-correlation of 0.95 for joint angles. For standardized occupational risk classification – adequate. For segment-level spine analysis – not what the approach is designed for.

Koca & Koca (2025) distributed five IMU sensors along the entire spine (C1, C7, T5, T12, L5) and trained ML models for lordosis/kyphosis classification. Balanced accuracies: 0.55 to 0.82. The authors explicitly call their results "exploratory indicators." Five sensors, machine learning – and it stays at approximations. A smartphone at one point delivers correspondingly less. That is not a product weakness. That is physics.

Property	Airgo XP (1 IMU)	Rectify FlexTail
Measurement points	1 device on the back	18 nodes along the spine
Lordosis detectable	No	Yes, segment-level
Torsion detectable	No	Yes
Lateral flexion	Coarse (whole segment)	Segment-specific
Shoulder position	No	Yes
Suited for	Shift-level posture classification	Individual spine geometry, targeted interventions

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FAQ: Smartphone Included? Cost? Can You Use Them Separately?

Does the Airgo XP include a smartphone? Yes – the Airgo XP is the Samsung Galaxy XCover 7 with the suitX app and a body mounting. No separate device needed.

Can you use IX BACK AIR or VOLTON without Airgo XP? Yes, easily. The exoskeletons are standalone products. Airgo XP is a separately bookable analytics add-on – neither depends on the other.

What does the system cost? suitX does not publish list prices. Inquiries go through Ottobock's sales team. Leasing models are common in the industry.

When are there enough data for meaningful analysis? suitX recommends at least six months of use before drawing reliable conclusions.

What is the difference between Airgo XP and MotionMiners? MotionMiners is an independent company based in Dortmund with its own hardware – dedicated wrist sensors and a belt clip, no smartphone. In cooperation with suitX they offer "Bionic Analytics": 6–8 weeks of Paexo Back use combined with 15 working days of MotionMiners measurement, with and without the exoskeleton. That is a separate analytics offering – not part of the standard Airgo XP package.

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Side-by-Side Comparison: Airgo XP vs. Rectify FlexTail

Criterion	Airgo XP (Samsung XCover 7)	Rectify FlexTail
Measurement method	IMU – tilt angle	Flex sensors / distributed nodes – 3D geometry
Measurement points	1 device on the back	18 nodes along the spine
Lordosis	No	Yes
Torsion	No	Yes
Lateral flexion	Coarse	Segment-specific
Shoulder position	No	Yes
Form factor	Smartphone clip	Integrated into compression shirt (rectify.de)
Analysis goal	Shift assessment, activity risk profile	Individual spine geometry
Independent validation	No peer-reviewed study on Airgo XP found	Available depending on system

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Which Approach Is Right for Whom?

The decision comes down to what question you are trying to answer.

"In which activities and how often is my workforce under heavy physical load?" Airgo XP handles this well. You get shift-level assessments, posture classification by workstation, and bending counts per activity. That is enough to prioritize workplaces and manage exoskeleton deployment.

"Why does employee X have recurring complaints in a specific lumbar segment despite similar overall load?" This is where a single IMU reaches its limits. The Rectify FlexTail – a sensor integrated into a compression shirt with 18 measurement nodes – covers exactly this: lumbar lordosis, torsion, lateral flexion and sagittal tilt, segment by segment, in real time. For individual spine mechanics, it is the right tool.

One more thing: exoskeleton and analytics solve different problems. The exoskeleton offloads mechanically – independent of the analytics quality. For shift-level assessments and activity risk profiles, Airgo XP is a solid starting point. For individual spine mechanics and targeted interventions, Rectify is the better fit – because the hardware measures the problem directly, instead of estimating it.

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Sources

1. suitX by Ottobock. Airgo XP product page (archived December 2025). https://web.archive.org/web/20251219010614/https://www.suitx.com/en/products/airgo-xp
2. González-Alonso et al. (2026). Development of an end-to-end hardware and software pipeline for affordable and feasible ergonomics assessment in the automotive industry. arXiv:2601.17574.
3. Koca, Koca (2025). Anatomy-Based Assessment of Spinal Posture Using IMU Sensors and Machine Learning. Sensors (Basel), 25(19):5963. DOI: 10.3390/s25195963.
4. Schmalz T, Bellmann M, Reimer K, Ernst M. (2022). A Passive Back-Support Exoskeleton for Manual Materials Handling. IISE Transactions on Occupational Ergonomics and Human Factors, 10(1):7-20. DOI: 10.1080/24725838.2021.1950951.
5. Luger T et al. (2023). Using a Back Exoskeleton During Industrial and Functional Tasks. Human Factors, 65(1):5-21. DOI: 10.1177/00187208211007267.
6. Jakobsen MD et al. (2024). In-Field Training of a Passive Back Exoskeleton Changes the Biomechanics of Logistic Workers. IISE Transactions on Occupational Ergonomics and Human Factors, 12(3):149-161. PMID: 38869954.
7. Zheng L et al. (2024). Evaluation of a passive back-support exoskeleton during in-bed patient handling. International Journal of Occupational Safety and Ergonomics, 30(4):1226-1233. PMID: 39154219.