Sagi Giterman

Qualisys launches Prisma Pose, a proprietary markerless skeletal tracking engine built directly into QTM - eliminating third-party software, unifying markerless output with force plate and EMG data, and giving biomechanics labs a complete markerless motion capture solution.

The walking you want to characterise often happens outside the camera volume. Xsens sets out what wearable inertial capture adds to gait research, how to evaluate a system, and where the accuracy numbers actually sit against optical reference.

EMG reveals which hamstring muscles are recruited during common rehabilitation exercises, exposing asymmetries and compensations that help practitioners reduce injury risk and guide smarter program design.

High-density surface EMG reveals that children with Developmental Coordination Disorder use more fixed motor-unit firing strategies than typically developing peers - a neuromuscular biomarker that could reshape how DCD is understood and treated.

At a leading rehabilitation centre in Lyon, a Qualisys gait lab and an immersive virtual environment are used daily to support treatment, rehabilitation and injury prevention, and to make the case for routine musculoskeletal check-ups.

EMG reveals what visual assessment cannot, which muscles are active, how strongly they contribute, and how patterns shift across exercises. Delsys shows how Trigno Analytics enables data-driven exercise selection and return-to-play decisions.

Discover how Luxembourg's SportFabrik, one of Europe's most advanced biomechanics facilities, used Qualisys motion capture, 16 force plates, and integrated EMG to help professional basketball player Magaly Meynadier return to elite competition after a career-threatening knee injury.

A closer look at how the Ariel Fischer Lab at the Technion – Israel Institute of Technology is using the AMTI Instrumented Treadmill for high-precision gait analysis and biomechanical research.

Qualisys has officially launched OnTraq, a markerless analysis system that lets elite sports organizations assess a full roster of 20 athletes in just 30 minutes, delivering accurate, repeatable functional data without specialist operation.

EMG pattern recognition translates muscle signals into prosthetic movements, enabling more natural limb function for patients with upper-limb deficiencies. Two recent studies demonstrate how input data quality and type significantly improve actuation accuracy in myoelectric prosthetics.

EMG-guided Human Robot Collaboration (HRC) enables automated optimization of worker posture and joint torque in industrial settings, reducing muscle effort and improving ergonomics during high-effort tasks.

Human-in-the-loop methods using EMG biosignals and machine learning are transforming wearable robotics, enabling more personalized assistive devices that reduce muscle effort and device abandonment.

MANUS gloves are now natively integrated into NVIDIA Isaac Lab 2.3, enabling researchers and robotics teams to capture high-fidelity demonstration data for robot policy training through natural hand teleoperation inside simulation.

A practical guide to using inertial motion capture for biomechanics research - covering how to capture reliable 3D kinematics in lab and field settings, choose the right system, and translate movement data into meaningful research outcomes.

Myoelectric-controlled lower limb prostheses use EMG signals to actuate movement, but assumptions about neural activation between residual and intact limbs may need revision. New research reveals that amputation alters motor unit properties in ways that directly impact prosthetic control models.

Electromyography-driven musculoskeletal models can track muscle fatigue in real-time, with applications in sports training, rehabilitation, and manual handling. This post explores a novel time-varying model (t-pEMS) that uses EMG data to estimate fatigue progression with person-specific accuracy.

By combining EMG and ultrasound imaging, neuromechanics research reveals how muscles activate and adapt mechanically and neurally - opening the door to personalized rehabilitation and deeper insights into individual movement signatures.

Delsys EMG systems help sports performance and rehabilitation professionals measure asymmetry, fatigue, compensation, and muscle inhibition in athletes - translating precise data into actionable insights for return-to-play decisions.

Cardiff University researchers combine TMS and Delsys EMG during dynamic walking tasks to reveal how the brain and spinal cord coordinate muscle activity in real-world movement, with direct applications in fall prevention and rehabilitation.

The Royal Melbourne Institute of Technology (RMIT) Uncrewed Aircraft Systems Research Team (RUASRT) set out to tackle a tough challenge: studying how kestrels master wind-hovering in turbulent conditions. Traditional tracking methods couldn’t provide the precise, high-speed kinematic data needed for Uncrewed Aerial Vehicle (UAV) stability research.