Hybrid Conferencee

International Conference on Clinical Biomechanics and Ergonomics (ICCBE - 26)

22nd - 23rd September 2026 | Geneva, Switzerland

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Certificate of Presentation:
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Networking with Global Experts:
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Keynote Speaker Sessions:
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Best Paper & Best Paper Presentation Award:
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SDG-Inspired Conference Focus:
"Our conference will highlight research that addresses global sustainability, inclusive education, and solutions for environmental challenges."

Conference Session Tracks

SDG Wheel

Aligned with

UN Sustainable Development Goals

This conference contributes to global sustainability by aligning its research discussions and academic sessions with key United Nations Sustainable Development Goals. It fosters knowledge exchange, innovation, and collaborative engagement.

SDG 3
SDG 3 Good Health and Well-being
SDG 4
SDG 4 Quality Education
SDG 8
SDG 8 Decent Work and Economic Growth
Track 01

Advancements in Clinical Biomechanics

This track focuses on the latest innovations in clinical biomechanics, emphasizing the integration of engineering principles in diagnosing and treating musculoskeletal disorders. Researchers are encouraged to present studies that highlight the impact of biomechanical analysis on patient outcomes.

Track 02

Ergonomics in Workplace Design

This session explores the role of ergonomics in optimizing workplace environments to enhance productivity and reduce injury risks. Contributions should address the application of ergonomic principles in various industries and their implications for worker health.

Track 03

Predictive Modeling in Biomedical Engineering

This track invites discussions on the development and application of predictive modeling techniques in biomedical contexts. Papers should focus on how these models can improve clinical decision-making and patient management.

Track 04

Machine Learning Applications in Biomechanics

This session highlights the use of supervised and unsupervised learning methods in analyzing biomechanical data. Researchers are encouraged to share findings on how machine learning can enhance understanding of human motion and injury prevention.

Track 05

Deep Learning for Human Motion Analysis

This track focuses on the application of deep learning techniques in the analysis of human motion. Contributions should demonstrate how these advanced algorithms can improve motion capture accuracy and biomechanical assessments.

Track 06

Anomaly Detection in Biomechanical Systems

This session addresses the challenges and methodologies associated with anomaly detection in biomechanical systems. Papers should explore innovative approaches to identifying deviations in normal biomechanical patterns and their clinical significance.

Track 07

Feature Extraction Techniques in Ergonomics

This track emphasizes the importance of feature extraction methods in ergonomic assessments and biomechanical studies. Researchers are invited to present novel techniques that enhance the analysis of ergonomic data.

Track 08

Workflow Automation in Clinical Settings

This session explores the integration of workflow automation technologies in clinical biomechanics and ergonomics. Contributions should discuss the impact of automation on efficiency, accuracy, and patient care.

Track 09

Industrial IoT and Predictive Maintenance

This track examines the role of Industrial Internet of Things (IoT) in predictive maintenance within biomedical engineering contexts. Papers should highlight case studies that demonstrate the benefits of IoT technologies in maintaining biomechanical systems.

Track 10

Digital Twin Technologies in Rehabilitation

This session focuses on the application of digital twin technologies in rehabilitation practices. Researchers are encouraged to present findings on how digital twins can enhance patient monitoring and treatment personalization.

Track 11

Process Optimization in Biomechanical Engineering

This track invites discussions on methodologies for process optimization in biomechanical engineering applications. Contributions should showcase innovative approaches that lead to improved efficiency and effectiveness in biomechanical interventions.