Home/Healthcare & Medical/Mercury Thermometer Usage Posture Correctness Classification Image Dataset
Mercury Thermometer Usage Posture Correctness Classification Image Dataset
#Image classification #posture recognition #Medical device detection #health monitoring #clinical research
- 5000 records
- 1.5G
- JPG/PNG/JSON
- CATL
MOBIUSI INC
Updated:2026-03-16
AI Analysis & Value Prop
In the current medical industry, temperature monitoring is one of the important health metrics, especially during pandemics, where the frequency of using thermometers has greatly increased. However, improper posture while using a mercury thermometer may lead to inaccurate measurement results, affecting health assessment. Existing solutions often rely on manual monitoring, which is inefficient and prone to errors. This dataset aims to use image classification technology to automatically recognize the usage posture of mercury thermometers, enhancing measurement accuracy. The dataset includes 5000 images of mercury thermometers in different postures, captured with high-definition cameras in well-lit environments to ensure image quality. After data collection, the images underwent multiple rounds of annotation and consistency checks to ensure the accuracy of each image's label, and they are finally stored in JPEG format for ease of subsequent processing and use.
Dataset Insights
Sample Examples
4f58e0ba**.jpg|980*1154|87.83 KB
a0cba958**.jpg|980*823|150.20 KB
2d708577**.jpg|980*1237|202.83 KB
8e24685f**.jpg|980*1308|141.65 KB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| pose_correctness | string | Indicates whether the usage pose of the mercury thermometer is correct. |
| hand_position | string | Identifies the position of the hand during the use of the mercury thermometer. |
Compliance Statement
| Authorization Type | Proprietary - Commercial AI Training License (No Redistribution) |
| Commercial Use | Requires exclusive subscription or authorization contract (monthly or per-invocation charging) |
| Privacy and Anonymization | No PII, no real company names, simulated scenarios follow industry standards |
| Compliance System | Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs |
Frequently Asked Questions
- In which healthcare scenarios is this dataset mainly used?
- This dataset is mainly used for detecting and recognizing the correct usage postures of mercury thermometers to improve the accuracy of temperature measurement, widely applied in health monitoring and training at medical institutions.
- How can this dataset be used to improve the service quality of healthcare institutions?
- By training machine learning models, this dataset can help healthcare institutions accurately recognize the correct postures for mercury thermometer usage, thus improving measurement accuracy and service quality.
- Why is the correct usage posture of a mercury thermometer important?
- The correct usage of a mercury thermometer ensures measurement accuracy, preventing misdiagnosis caused by incorrect readings and ensuring the reliability of health checks.
- What factors might affect the accuracy of mercury thermometer readings?
- Incorrect posture, changes in ambient temperature, and the quality of the thermometer can all affect the accuracy of mercury thermometer readings.
- How can image classification technology optimize the temperature measurement process?
- Image classification technology can automatically identify and alert users to correct incorrect thermometer usage postures, reducing human error and enhancing the efficiency of the measurement process.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Mercury Thermometer Usage Posture Correctness Classification Image Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/a31d50c94ab92081b6a4a52a65257b9e?dataset_scene_id=4},
urldate={2025-10-23},
keywords={mercury thermometer, image classification, medical dataset, health monitoring, posture recognition},
version={1.0}
}Using this in research? Please cite us.
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