Detecting Heart Rate From Virtual Reality Headset-Embedded Inertial Sensors: a Kinetic Energy Approach

2021 ◽  
Author(s):  
S. Solbiati ◽  
A. Buffoli ◽  
V. Megale ◽  
G. Damato ◽  
B. Lenzi ◽  
...  
Keyword(s):  
Heart Rate ◽  
Virtual Reality ◽  
Kinetic Energy ◽  
Inertial Sensors ◽  
Energy Approach

scholarly journals Feasibility of Heart Rate and Respiratory Rate Estimation by Inertial Sensors Embedded in a Virtual Reality Headset

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7168
Author(s):  
Claudia Floris ◽  
Sarah Solbiati ◽  
Federica Landreani ◽  
Gianfranco Damato ◽  
Bruno Lenzi ◽  
...  
Keyword(s):  
Heart Rate ◽  
Virtual Reality ◽  
Respiratory Rate ◽  
Inertial Sensors ◽  
Rate Estimation ◽  
Power Spectral ◽  
The Subject ◽  
Controlled Breathing ◽  
The One ◽  
Electrocardiogram Ecg

Virtual reality (VR) headsets, with embedded micro-electromechanical systems, have the potential to assess the mechanical heart’s functionality and respiratory activity in a non-intrusive way and without additional sensors by utilizing the ballistocardiographic principle. To test the feasibility of this approach for opportunistic physiological monitoring, thirty healthy volunteers were studied at rest in different body postures (sitting (SIT), standing (STAND) and supine (SUP)) while accelerometric and gyroscope data were recorded for 30 s using a VR headset (Oculus Go, Oculus, Microsoft, USA) simultaneously with a 1-lead electrocardiogram (ECG) signal for mean heart rate (HR) estimation. In addition, longer VR acquisitions (50 s) were performed under controlled breathing in the same three postures to estimate the respiratory rate (RESP). Three frequency-based methods were evaluated to extract from the power spectral density the corresponding frequency. By the obtained results, the gyroscope outperformed the accelerometer in terms of accuracy with the gold standard. As regards HR estimation, the best results were obtained in SIT, with Rs2 (95% confidence interval) = 0.91 (0.81−0.96) and bias (95% Limits of Agreement) −1.6 (5.4) bpm, followed by STAND, with Rs2 = 0.81 (0.64−0.91) and −1.7 (11.6) bpm, and SUP, with Rs2 = 0.44 (0.15−0.68) and 0.2 (19.4) bpm. For RESP rate estimation, SUP showed the best feasibility (98%) to obtain a reliable value from each gyroscope axis, leading to the identification of the transversal direction as the one containing the largest breathing information. These results provided evidence of the feasibility of the proposed approach with a degree of performance and feasibility dependent on the posture of the subject, under the conditions of keeping the head still, setting the grounds for future studies in real-world applications of HR and RESP rate measurement through VR headsets.

scholarly journals Wearable Technologies in Field Hockey Competitions: A Scoping Review

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5242
Author(s):  
Jolene Ziyuan Lim ◽  
Alexiaa Sim ◽  
Pui Wah Kong
Keyword(s):  
Heart Rate ◽  
Inertial Sensors ◽  
Wearable Devices ◽  
Field Hockey ◽  
Heart Rate Monitors ◽  
Search Terms ◽  
Physiological Demands ◽  
And Performance ◽  
Future Work ◽  
Skin Temperatures

The aim of this review is to investigate the common wearable devices currently used in field hockey competitions, and to understand the hockey-specific parameters these devices measure. A systematic search was conducted by using three electronic databases and search terms that included field hockey, wearables, accelerometers, inertial sensors, global positioning system (GPS), heart rate monitors, load, performance analysis, player activity profiles, and competitions from the earliest record. The review included 39 studies that used wearable devices during competitions. GPS units were found to be the most common wearable in elite field hockey competitions, followed by heart rate monitors. Wearables in field hockey are mostly used to measure player activity profiles and physiological demands. Inconsistencies in sampling rates and performance bands make comparisons between studies challenging. Nonetheless, this review demonstrated that wearable devices are being used for various applications in field hockey. Researchers, engineers, coaches, and sport scientists can consider using GPS units of higher sampling rates, as well as including additional variables such as skin temperatures and injury associations, to provide a more thorough evaluation of players’ physical and physiological performances. Future work should include goalkeepers and non-elite players who are less studied in the current literature.

scholarly journals Multiclass emotion prediction using heart rate and virtual reality stimuli

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Aaron Frederick Bulagang ◽  
James Mountstephens ◽  
Jason Teo
Keyword(s):  
Heart Rate ◽  
Virtual Reality ◽  
Nearest Neighbor ◽  
Subject Classification ◽  
Support Vector ◽  
Display Device ◽  
K Nearest Neighbor ◽  
Potential Applications ◽  
Health Rehabilitation ◽  
Emotion Model

Abstract Background Emotion prediction is a method that recognizes the human emotion derived from the subject’s psychological data. The problem in question is the limited use of heart rate (HR) as the prediction feature through the use of common classifiers such as Support Vector Machine (SVM), K-Nearest Neighbor (KNN) and Random Forest (RF) in emotion prediction. This paper aims to investigate whether HR signals can be utilized to classify four-class emotions using the emotion model from Russell’s in a virtual reality (VR) environment using machine learning. Method An experiment was conducted using the Empatica E4 wristband to acquire the participant’s HR, a VR headset as the display device for participants to view the 360° emotional videos, and the Empatica E4 real-time application was used during the experiment to extract and process the participant's recorded heart rate. Findings For intra-subject classification, all three classifiers SVM, KNN, and RF achieved 100% as the highest accuracy while inter-subject classification achieved 46.7% for SVM, 42.9% for KNN and 43.3% for RF. Conclusion The results demonstrate the potential of SVM, KNN and RF classifiers to classify HR as a feature to be used in emotion prediction in four distinct emotion classes in a virtual reality environment. The potential applications include interactive gaming, affective entertainment, and VR health rehabilitation.

Effect of Virtual Reality Graded Exposure on Heart Rate and Self-Reported Anxiety Levels of Performing Saxophonists

2003 ◽  
Vol 51 (4) ◽  
pp. 302-315 ◽  
Author(s):  
Evelyn K. Orman
Keyword(s):  
Heart Rate ◽  
Virtual Reality ◽  
Virtual Environments ◽  
Exposure Period ◽  
Sense Of Presence ◽  
Graded Exposure ◽  
Subjective Measurements ◽  
Anxiety Levels ◽  
Exposure Sessions ◽  
Virtual Reality Exposure

This study is an examination of the effect of computer-generated virtual reality graded exposure on the physiological and psychological responses of performing musicians. Eight university saxophone majors, five men and three women, participated in twelve 15- to 20-minute weekly practice sessions during which they were immersed in one of four different virtual environments designed to elicit various anxiety levels. Baseline heart rates and subjective measurements were taken prior to immersion and continued throughout the exposure period. In addition, heart rate and subjective measurements were recorded for three live performances given by each subject before beginning the virtual reality exposure and after completion of the sixth and the twelfth exposure sessions. Findings indicated that the virtual environments did elicit a sense of presence and may have provided the means for desensitization. Heart-rate readings and psychological indications of anxiety did not always correspond.

Natural Locomotion Based on Foot-Mounted Inertial Sensors in a Wireless Virtual Reality System

2015 ◽  
Vol 24 (4) ◽  
pp. 298-321 ◽  
Author(s):  
Ernesto de la Rubia ◽  
Antonio Diaz-Estrella
Keyword(s):  
Virtual Reality ◽  
Gait Cycle ◽  
Inertial Sensors ◽  
Low Cost ◽  
Point Of View ◽  
Handheld Devices ◽  
Preliminary Evaluation ◽  
Virtual Reality System ◽  
Object Searching

Virtual reality has become a promising field in recent decades, and its potential now seems clearer than ever. With the development of handheld devices and wireless technologies, interest in virtual reality is also increasing. Therefore, there is an accompanying interest in inertial sensors, which can provide such advantages as small size and low cost. Such sensors can also operate wirelessly and be used in an increasing number of interactive applications. An example related to virtual reality is the ability to move naturally through virtual environments. This is the objective of the real-walking navigation technique, for which a number of advantages have previously been reported in terms of presence, object searching, and collision, among other concerns. In this article, we address the use of foot-mounted inertial sensors to achieve real-walking navigation in a wireless virtual reality system. First, an overall description of the problem is presented. Then, specific difficulties are identified, and a corresponding technique is proposed to overcome each: tracking of foot movements; determination of the user’s position; percentage estimation of the gait cycle, including oscillating movements of the head; stabilization of the velocity of the point of view; and synchronization of head and body yaw angles. Finally, a preliminary evaluation of the system is conducted in which data and comments from participants were collected.

670. Heart Rate Variability Responses to a Standardized Virtual Reality Exposure in Veterans with PTSD

2017 ◽  
Vol 81 (10) ◽  
pp. S271 ◽  
Author(s):  
Samuel Ridout ◽  
Christopher Spofford ◽  
Mascha van ׳t Wout ◽  
William Unger ◽  
Noah Philip ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Virtual Reality ◽  
Virtual Reality Exposure

scholarly journals Wearable Sensors Integrated with Virtual Reality: A Self-Guided Healthcare System Measuring Shoulder Joint Mobility for Frozen Shoulder

2019 ◽  
Vol 2019 ◽  
pp. 1-6 ◽  
Author(s):  
Jianjun Cui ◽  
Shih-Ching Yeh ◽  
Si-Huei Lee
Keyword(s):  
Virtual Reality ◽  
Shoulder Joint ◽  
Inertial Sensors ◽  
Wearable Sensors ◽  
Frozen Shoulder ◽  
Joint Mobility ◽  
Joint Movement ◽  
Rehabilitation Process ◽  
Shoulder Condition ◽  
At Home

Frozen shoulder is a common clinical shoulder condition. Measuring the degree of shoulder joint movement is crucial to the rehabilitation process. Such measurements can be used to evaluate the severity of patients’ condition, establish rehabilitation goals and appropriate activity difficulty levels, and understand the effects of rehabilitation. Currently, measurements of the shoulder joint movement degree are typically conducted by therapists using a protractor. However, along with the growth of telerehabilitation, measuring the shoulder joint mobility on patients’ own at home will be needed. In this study, wireless inertial sensors were combined with the virtual reality interactive technology to provide an innovative shoulder joint mobility self-measurement system that can enable patients to measure their performance of four shoulder joint movements on their own at home. Pilot clinical trials were conducted with 25 patients to confirm the feasibility of the system. In addition, the results of correlation and differential analyses compared with the results of traditional measurement methods exhibited a high correlation, verifying the accuracy of the proposed system. Moreover, according to interviews with patients, they are confident in their ability to measure shoulder joint mobility themselves.

scholarly journals Feasibility of a Commercially Available Virtual Reality System to Achieve Exercise Guidelines in Youth With Spina Bifida: Mixed Methods Case Study (Preprint)

2020 ◽  
Author(s):  
Byron Lai ◽  
Drew Davis ◽  
Mai Narasaki-Jara ◽  
Betsy Hopson ◽  
Danielle Powell ◽  
...  
Keyword(s):  
Physical Activity ◽  
Heart Rate ◽  
Virtual Reality ◽  
Spina Bifida ◽  
Moderate Intensity ◽  
Full Time ◽  
Heart Rate Monitor ◽  
Intervention Protocol ◽  
Exercise Guidelines ◽  
Total Average

BACKGROUND Access to physical activity among youth with spina bifida (SB) is much lower than it is for children without disability. Enjoyable home-based exercise programs are greatly needed. OBJECTIVE Our objective is to examine the feasibility of a virtual reality (VR) active video gaming system (ie, bundle of consumer-available equipment) to meet US physical activity guidelines in two youth with SB. METHODS Two youth with SB—a 12-year-old female and a 13-year-old male; both full-time wheelchair users—participated in a brief, 4-week exercise program using a popular VR head-mounted display: Oculus Quest (Facebook Technologies). The system included a Polar H10 (Polar Canada) Bluetooth heart rate monitor, a no-cost mobile phone app (VR Health Exercise Tracker [Virtual Reality Institute of Health and Exercise]), and 13 games. The intervention protocol was conducted entirely in the homes of the participants due to the coronavirus disease 2019 (COVID-19) pandemic. The VR system was shipped to participants and they were instructed to do their best to complete 60 minutes of moderate-intensity VR exercise per day. Exercise duration, intensity, and calories expended were objectively monitored and recorded during exercise using the heart rate monitor and a mobile app. Fatigue and depression were measured via self-report questionnaires at pre- and postintervention. Participants underwent a semistructured interview with research staff at postintervention. RESULTS Across the intervention period, the total average minutes of all exercise performed each week for participants 1 and 2 were 281 (SD 93) and 262 (SD 55) minutes, respectively. The total average minutes of moderate-intensity exercise performed per week for participants 1 and 2 were 184 (SD 103) (184/281, 65.4%) and 215 (SD 90) (215/262, 82.1%) minutes, respectively. One participant had a reduction in their depression score, using the Quality of Life in Neurological Disorders (Neuro-QoL) test, from baseline to postintervention, but no other changes were observed for fatigue and depression scores. Participants reported that the amount of exercise they completed was far higher than what was objectively recorded, due to usability issues with the chest-worn heart rate monitor. Participants noted that they were motivated to exercise due to the enjoyment of the games and VR headset as well as support from a caregiver. CONCLUSIONS This study demonstrated that two youth with SB who used wheelchairs could use a VR system to independently and safely achieve exercise guidelines at home. Study findings identified a promising protocol for promoting exercise in this population and this warrants further examination in future studies with larger samples.

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