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e4 hr signal  (Empatica Inc)

 
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    Empatica Inc e4 hr signal
    E4 Hr Signal, supplied by Empatica Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/e4 hr signal/product/Empatica Inc
    Average 90 stars, based on 1 article reviews
    e4 hr signal - by Bioz Stars, 2026-03
    90/100 stars

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    The block diagram of the stress level detection system for Samsung Gear S and S2 and Empatica <t>E4.</t> Since the sensors and platforms are different, please note <t>that</t> <t>EDA</t> and temperature signals are only available for E4.
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    The block diagram of the stress level detection system for Samsung Gear S and S2 and Empatica E4. Since the sensors and platforms are different, please note that EDA and temperature signals are only available for E4.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Continuous Stress Detection Using Wearable Sensors in Real Life: Algorithmic Programming Contest Case Study

    doi: 10.3390/s19081849

    Figure Lengend Snippet: The block diagram of the stress level detection system for Samsung Gear S and S2 and Empatica E4. Since the sensors and platforms are different, please note that EDA and temperature signals are only available for E4.

    Article Snippet: With all algorithms, HR, EDA and ACC signal combination with Empatica E4 devices had higher accuracy than with all devices in person-specific models.

    Techniques: Blocking Assay

    Decomposed EDA Signal from Empatica E4 wristband by applying cvxEDA tool.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Continuous Stress Detection Using Wearable Sensors in Real Life: Algorithmic Programming Contest Case Study

    doi: 10.3390/s19081849

    Figure Lengend Snippet: Decomposed EDA Signal from Empatica E4 wristband by applying cvxEDA tool.

    Article Snippet: With all algorithms, HR, EDA and ACC signal combination with Empatica E4 devices had higher accuracy than with all devices in person-specific models.

    Techniques:

    Stress with context classification accuracy, f-Measure, precision and recall values with different ML algorithms: three-class. HR + EDA +ACC for Empatica E4.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Continuous Stress Detection Using Wearable Sensors in Real Life: Algorithmic Programming Contest Case Study

    doi: 10.3390/s19081849

    Figure Lengend Snippet: Stress with context classification accuracy, f-Measure, precision and recall values with different ML algorithms: three-class. HR + EDA +ACC for Empatica E4.

    Article Snippet: With all algorithms, HR, EDA and ACC signal combination with Empatica E4 devices had higher accuracy than with all devices in person-specific models.

    Techniques:

    Stress with context classification accuracy, f-Measure, precision and recall values with different ML algorithms: three-class. HR +ACC for Empatica E4.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Continuous Stress Detection Using Wearable Sensors in Real Life: Algorithmic Programming Contest Case Study

    doi: 10.3390/s19081849

    Figure Lengend Snippet: Stress with context classification accuracy, f-Measure, precision and recall values with different ML algorithms: three-class. HR +ACC for Empatica E4.

    Article Snippet: With all algorithms, HR, EDA and ACC signal combination with Empatica E4 devices had higher accuracy than with all devices in person-specific models.

    Techniques:

    Effect of the used device to three-class stress with context classification accuracy when heart activity and accelerometer data are used together.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Continuous Stress Detection Using Wearable Sensors in Real Life: Algorithmic Programming Contest Case Study

    doi: 10.3390/s19081849

    Figure Lengend Snippet: Effect of the used device to three-class stress with context classification accuracy when heart activity and accelerometer data are used together.

    Article Snippet: With all algorithms, HR, EDA and ACC signal combination with Empatica E4 devices had higher accuracy than with all devices in person-specific models.

    Techniques: Activity Assay

    Effect of the device used to three-class stress level classification accuracy when only heart activity signal is used (without context).

    Journal: Sensors (Basel, Switzerland)

    Article Title: Continuous Stress Detection Using Wearable Sensors in Real Life: Algorithmic Programming Contest Case Study

    doi: 10.3390/s19081849

    Figure Lengend Snippet: Effect of the device used to three-class stress level classification accuracy when only heart activity signal is used (without context).

    Article Snippet: With all algorithms, HR, EDA and ACC signal combination with Empatica E4 devices had higher accuracy than with all devices in person-specific models.

    Techniques: Activity Assay

    Classification accuracies of Empatica E4 when removed inter-beat interval artifacts are replaced with interpolation vs. when they are removed.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Continuous Stress Detection Using Wearable Sensors in Real Life: Algorithmic Programming Contest Case Study

    doi: 10.3390/s19081849

    Figure Lengend Snippet: Classification accuracies of Empatica E4 when removed inter-beat interval artifacts are replaced with interpolation vs. when they are removed.

    Article Snippet: With all algorithms, HR, EDA and ACC signal combination with Empatica E4 devices had higher accuracy than with all devices in person-specific models.

    Techniques:

    Classification accuracies of general and person-specific models.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Continuous Stress Detection Using Wearable Sensors in Real Life: Algorithmic Programming Contest Case Study

    doi: 10.3390/s19081849

    Figure Lengend Snippet: Classification accuracies of general and person-specific models.

    Article Snippet: With all algorithms, HR, EDA and ACC signal combination with Empatica E4 devices had higher accuracy than with all devices in person-specific models.

    Techniques:

    Classification accuracies comparison of subjective report and known context. On the left, known context information (Free,1; Lecture, 2; Contest, 3) was used as class labels. On the right, subjective ground truths are used as class labels.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Continuous Stress Detection Using Wearable Sensors in Real Life: Algorithmic Programming Contest Case Study

    doi: 10.3390/s19081849

    Figure Lengend Snippet: Classification accuracies comparison of subjective report and known context. On the left, known context information (Free,1; Lecture, 2; Contest, 3) was used as class labels. On the right, subjective ground truths are used as class labels.

    Article Snippet: With all algorithms, HR, EDA and ACC signal combination with Empatica E4 devices had higher accuracy than with all devices in person-specific models.

    Techniques: