arXiv AI July 7, 2026 By Andreas Spilz, Heiko Oppel, Michael Munz

Boosting Automatic Exercise Evaluation Through Musculoskeletal Simulation-Based IMU Data Augmentation

arXiv:2505. 24415v2 Announce Type: replace-cross Abstract: Automated evaluation of movement quality can enhance physiotherapeutic treatment and sports training by providing objective, real-time feedback.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

fine-tuning

arXiv Machine Learning

Jul 20

A Standardized Benchmark for Skeleton-Based Rehabilitation Assessment Using Deep Learning

arXiv:2507. 21018v2 Announce Type: replace-cross Abstract: Automated assessment of human motion plays a vital role in rehabilitation, enabling objective evaluation of patient performance and progress.

By Ali Ismail-Fawaz, Maxime Devanne, Stefano Berretti, Jonathan Weber, Germain Forestier

benchmarks

arXiv AI

Jul 7

Domain Knowledge-Informed Self-Supervised Representations for Workout Form Assessment

arXiv:2202. 14019v3 Announce Type: replace-cross Abstract: Maintaining proper form while exercising is important for preventing injuries and maximizing muscle mass gains.

By Paritosh Parmar, Amol Gharat, Helge Rhodin

computer-vision fine-tuning

arXiv Machine Learning

Jul 7

Representing and Detecting Label Ambiguity in IMU-Based Exercise Evaluation

arXiv:2607. 04842v1 Announce Type: new Abstract: Home-based physiotherapy is performed without supervision, which leads to incorrect execution and motivates systems that assess movement automatically from inertial measurement units (IMUs).

By Andreas Spilz, Heiko Oppel, Michael Munz

arXiv Machine Learning

Jul 13

Data-Efficient Deep Learning: Empirical Guidelines for Training Set Size Estimation in Inertial Sensor Classification

arXiv:2607. 09402v1 Announce Type: new Abstract: Deep learning models dependency on large-scale inertial datasets presents a significant bottleneck in inertial sensor-based classification tasks, such as human activity recognition and smartphone location recognition.

By Ofir Kruzel, Itzik Klien

arXiv AI

Jul 10

Pose-to-Biomechanics: Bridging 3D Human Pose Estimation and Biomechanical Attribute Prediction

arXiv:2607. 08725v1 Announce Type: cross Abstract: Recent progress in 3D human pose estimation has made markerless recovery of skeletal motion increasingly accurate and scalable.

By Ayda Eghbalian, Kevin Desai

llms computer-vision multimodal benchmarks

arXiv AI

2d ago

GenGait: A Transformer-Based Model for Human Gait Anomaly Detection and Normative Twin Generation

arXiv:2604.01997v2 Announce Type: replace Abstract: Gait analysis provides an objective characterization of locomotor function and is widely used to support diagnosis and rehabilitation monitoring ac...

By Elisa Motta, Marta Lorenzini, Clara Mouawad, Alberto Ranavolo, Mariano Serrao, Arash Ajoudani

llms

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A Standardized Benchmark for Skeleton-Based Rehabilitation Assessment Using Deep Learning

Domain Knowledge-Informed Self-Supervised Representations for Workout Form Assessment

Representing and Detecting Label Ambiguity in IMU-Based Exercise Evaluation

Data-Efficient Deep Learning: Empirical Guidelines for Training Set Size Estimation in Inertial Sensor Classification

Pose-to-Biomechanics: Bridging 3D Human Pose Estimation and Biomechanical Attribute Prediction

GenGait: A Transformer-Based Model for Human Gait Anomaly Detection and Normative Twin Generation