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. 2020 Jan 28;20(3):718.
doi: 10.3390/s20030718.

Wearable Emotion Recognition Using Heart Rate Data from a Smart Bracelet

Lin Shu  1 , Yang Yu  1 , Wenzhuo Chen  1 , Haoqiang Hua  1   2 , Qin Li  3 , Jianxiu Jin  1 , Xiangmin Xu  1
Affiliations

Wearable Emotion Recognition Using Heart Rate Data from a Smart Bracelet

Lin Shu et al. Sensors (Basel). .

Abstract

Emotion recognition and monitoring based on commonly used wearable devices can play an important role in psychological health monitoring and human-computer interaction. However, the existing methods cannot rely on the common smart bracelets or watches for emotion monitoring in daily life. To address this issue, our study proposes a method for emotional recognition using heart rate data from a wearable smart bracelet. A 'neutral + target' pair emotion stimulation experimental paradigm was presented, and a dataset of heart rate from 25 subjects was established, where neutral plus target emotion (neutral, happy, and sad) stimulation video pairs from China's standard Emotional Video Stimuli materials (CEVS) were applied to the recruited subjects. Normalized features from the data of target emotions normalized by the baseline data of neutral mood were adopted. Emotion recognition experiment results approved the effectiveness of 'neutral + target' video pair simulation experimental paradigm, the baseline setting using neutral mood data, and the normalized features, as well as the classifiers of Adaboost and GBDT on this dataset. This method will promote the development of wearable consumer electronic devices for monitoring human emotional moods.

Keywords: emotion recognition; heart rate; smart bracelet; wearable.

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Conflict of interest statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Figures

Figure 1
Figure 1
Scenes from the selected videos with its corresponding emotional response: (a–c) neutral; (d–f) sad; (g–i) happy. CEVS permission obtained [20].
Figure 2
Figure 2
Experimental setup: The heart rate signal of the subject was collected using a smart bracelet (Algoband F8), and the sampling rate of the bracelet was 25 Hz: (a) The bracelet was worn on the subject’s wrist; (b) Connection and data recording APP via Bluetooth.
Figure 3
Figure 3
Steps of the experiment.
Figure 4
Figure 4
Typical heart rate data of the three stimulated emotional states (The horizontal axis is time in seconds and the vertical axis is heart rate in beats per minute): (a) neutral, (b) happy, (c) sad.
Figure 5
Figure 5
Steps of data processing.
Figure 6
Figure 6
Typical Heart rate parameters for feature extraction: (1) Up_Amplitude. (2) Up_Time. (3) Down_Amplitude. (4) Slope. (5) T_Continue.
Figure 7
Figure 7
Normalized signal and its 25-mean data: (a) normalized signal, (b) 25_mean data.
Figure 8
Figure 8
Classification result of happy and neutral emotions.
Figure 9
Figure 9
Classification result of sad and neutral emotions.
Figure 10
Figure 10
Classification result of happy and sad emotions.
Figure 11
Figure 11
Classification result of neutral, happy and sad emotions.
See this image and copyright information in PMC

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