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Related Concept Videos

Data Collection by Experiments01:13

Data Collection by Experiments

Data collection is a systematic method of obtaining, observing, measuring, and analyzing accurate information. An experimental study is a standard method of data collection that involves the manipulation of the samples by applying some form of treatment prior to data collection. It refers to manipulating one variable to determine its changes on another variable. The sample subjected to treatment is known as “experimental units.”
An example of the experimental method is a public clinical trial...
Data Collection by Observations01:08

Data Collection by Observations

Data collection refers to a systematic way of obtaining, observing, measuring, and analyzing accurate information. Observational studies are one of the most widely used methods of data collection. It involves collecting data by observing the behavior and physical characteristics of a sample without making any modifications to the sample.
An astronomer viewing the motion and brightness of stars in the sky and recording the data is an example of observational data collection. A botanist recording...
Data Collection I01:30

Data Collection I

Data collection gathers information needed to make accurate judgments about a patient's present condition. During a health history interview, subjective data is collected from the patient, their caregivers, or family members, and objective data is collected through observations and physical assessment. Patients are the primary source of subjective data. Thus information gathered from patients through interviews, observations, and physical examination is primary data. Secondary sources of data...
Data Reporting and Recording01:24

Data Reporting and Recording

Reporting and recording are crucial in data documentation. The timely, thorough, and accurate documentation of facts is essential when recording patient data. Failure to record findings during an assessment or interpretation of a problem will result in loss of information and make the patient document unreliable. The reader is left with general impressions if the information is not specific. A recording is documenting data of the individual's health information in a traceable, secure, and...

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Related Experiment Video

Updated: May 14, 2026

Interactive and Visualized Online Experimentation System for Engineering Education and Research
08:35

Interactive and Visualized Online Experimentation System for Engineering Education and Research

Published on: November 24, 2021

Everyday Activity Science and Engineering Table Setting Dataset.

Moritz Meier1, Yale Hartmann1, Yasmina El Ouahabi1

  • 1University Bremen, Cognitive Systems Lab (CSL), Bremen, 28359, Germany.

Scientific Data
|May 12, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces the Everyday Activity Science and Engineering Table Setting Dataset (EASE-TSD), a rich multimodal biosignal resource. It enables research into human activity planning and execution for advanced robotics and cognitive systems.

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Methods for Presenting Real-world Objects Under Controlled Laboratory Conditions
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Methods for Presenting Real-world Objects Under Controlled Laboratory Conditions

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Last Updated: May 14, 2026

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Methods for Presenting Real-world Objects Under Controlled Laboratory Conditions
06:54

Methods for Presenting Real-world Objects Under Controlled Laboratory Conditions

Published on: June 21, 2019

Area of Science:

  • Cognitive Science
  • Robotics
  • Human-Computer Interaction
  • Biomedical Engineering

Background:

  • Understanding human activity planning is vital for developing intelligent systems.
  • Existing datasets often lack multimodal biosignal richness for complex task analysis.

Purpose of the Study:

  • To introduce and validate the Everyday Activity Science and Engineering Table Setting Dataset (EASE-TSD).
  • To provide a comprehensive multimodal dataset for studying human activity planning and execution.

Main Methods:

  • Collected multimodal biosignals (motion capture, video, eye-tracking, EMG, EDA, EEG, etc.) from 78 participants setting a table.
  • Synchronously recorded eight high-dimensional biosignal streams.
  • Annotated data with activity phases, actions, motions, objects, and think-aloud protocols.

Main Results:

  • The EASE-TSD dataset comprises 78 sessions with six table-setting trials each.
  • Data includes synchronized motion capture, video, eye-tracking, EMG, EDA, EEG, and audio.
  • Comprehensive 3-level annotations and think-aloud protocols are provided.

Conclusions:

  • EASE-TSD offers a valuable resource for advancing research in human activity understanding.
  • The dataset facilitates the development of cognition-enabled robots and AI systems.
  • Leverages advanced biosignal processing and machine learning for analysis.