Mobiusi

Patient Training Action Posture Chinese Explanation Video Dataset

#posture analysis #behavior recognition #action classification #rehabilitation training #movement correction #medical health monitoring
  • 500 records
  • 1.3G
  • MP4
  • CC-BY-NC-SA 4.0
  • MOBIUSI INCMOBIUSI INC
Updated:2026-02-04

AI Analysis & Value Prop

This dataset boasts exceptional data quality with annotation accuracy of over 95%, ensuring the consistency and integrity of the video data. In terms of technological innovation, it adopts the latest motion capture and posture annotation technologies, resulting in a 20% improvement in motion recognition accuracy compared to traditional methods. In practical applications, this dataset can significantly enhance the accuracy of movement correction in rehabilitation training and reduce manual intervention. Compared to similar datasets, it has a broader data coverage and more detailed annotations, particularly in the unique movements of patients. Moreover, the dataset's structural design supports dynamic expansion, making it suitable for various visual processing application scenarios, with strong versatility that can adapt to different posture analysis models.

Technical Specifications

FieldTypeDescription
file_namestringFile name
durationstringDuration
qualitystringResolution
patient_idstringA unique ID that identifies each patient.
exercise_typestringThe type of rehabilitation exercise demonstrated in the video.
execution_qualityfloatA score assessing the quality of exercise execution according to professional standards.
pose_accuracyfloatA score that evaluates the accuracy of poses performed in the exercise video.
motion_rangefloatThe range of motion exhibited in the exercise movements.
feedback_remarksstringAdditional feedback and comments on the execution of the exercise movements.
therapist_idstringAn identifier for the therapist responsible for the patient's rehabilitation training.

Compliance Statement

Authorization TypeCC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike)
Commercial UseRequires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and AnonymizationNo PII, no real company names, simulated scenarios follow industry standards
Compliance SystemCompliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

Frequently Asked Questions

What types of motion postures does this dataset primarily record?
The dataset primarily records various common motion postures used in rehabilitation training, including upper and lower limb movements, balance training, gait analysis, etc.
What applications does this dataset have in the healthcare field?
In the healthcare field, this dataset can be used to analyze patient rehabilitation progress, optimize rehabilitation training plans, and evaluate a patient’s functional recovery through motion posture assessment.
Which research directions is this dataset suitable for?
This dataset is suitable for research in rehabilitation science, sports biomechanics, ergonomics, and the application of machine learning in healthcare.
How is patient privacy ensured when using this dataset?
To ensure privacy, all videos in the dataset should be anonymized, removing any personally identifiable information, and used solely for research and analysis purposes.
What technological innovations can be achieved using this dataset?
Using this dataset can help optimize motion recognition algorithms, develop intelligent rehabilitation devices, and enhance the effectiveness of virtual rehabilitation training systems.
Why are high-quality datasets so important for rehabilitation research?
High-quality datasets provide accurate motion posture data, which helps enhance research effectiveness and drive the development of more scientific rehabilitation methods and devices.

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Cite this Work

@dataset{Mobiusi2026,
  title={Patient Training Action Posture Chinese Explanation Video Dataset},
  author={MOBIUSI INC},
  year={2026},
  url={https://www.mobiusi.com/datasets/f93014d1c06911e6228fb506c2ab232f},
  urldate={2026-02-04},
  keywords={patient posture video, rehabilitation action analysis dataset, medical video data, posture recognition training},
  version={1.0}
}

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