Heart rate variability (HRV) biofeedback training is known for its effectiveness in improving phy... more Heart rate variability (HRV) biofeedback training is known for its effectiveness in improving physical health, emotional health, and resilience by the ability to regulate heart rhythm. However, there are various challenges in delivering and interpreting the biofeedback information, which prevents an optimal experience. Therefore, this study presents the fundamentals of developing a real-time HRV biofeedback system using deep breathing exercise by exploring the minimum time window of RR-intervals resulting in a reliable analysis. Moreover, it investigates the appropriate HRV measures by examining the significant changes between resting and breathing conditions and the trends consistency across ultra-short-term segments. The overall results suggest that a minimum time window of 20-seconds can provide a reliable HRV time-domain analysis. Whereas the possible HRV measures that can be used in a real-time biofeedback system are SDNN, LF, and total power. These outcomes will contribute to ...
Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems, 2019
Heart rate variability (HRV) has become a wide-spread area for the investigation of the health an... more Heart rate variability (HRV) has become a wide-spread area for the investigation of the health and stress states of individuals. This paper aims at exploring the effectiveness of representing HRV measures with alternative modalities, other than visual displays, such as audio or haptics. Therefore, we undertook a preliminary study in which we applied a parameter mapping sonification approach to transform the HRV signal into an audible form. In this work, we sought to evaluate the human perception of the developed auditory interface. Hence, a dataset that involves interbeat interval measurements of individuals experiencing changes in mental state in the form of meditation was selected as the basis of the study. The HRV parameters of the dataset were mapped to acoustic features using a linear mapping technique. The feasibility of the system was assessed by measuring the learnability, performance, latency, and confidence aspects. The results suggest a great potential of incorporating au...
Heart rate variability (HRV) biofeedback training is known for its effectiveness in improving phy... more Heart rate variability (HRV) biofeedback training is known for its effectiveness in improving physical health, emotional health, and resilience by the ability to regulate heart rhythm. However, there are various challenges in delivering and interpreting the biofeedback information, which prevents an optimal experience. Therefore, this study presents the fundamentals of developing a real-time HRV biofeedback system using deep breathing exercise by exploring the minimum time window of RR-intervals resulting in a reliable analysis. Moreover, it investigates the appropriate HRV measures by examining the significant changes between resting and breathing conditions and the trends consistency across ultra-short-term segments. The overall results suggest that a minimum time window of 20-seconds can provide a reliable HRV time-domain analysis. Whereas the possible HRV measures that can be used in a real-time biofeedback system are SDNN, LF, and total power. These outcomes will contribute to ...
Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems, 2019
Heart rate variability (HRV) has become a wide-spread area for the investigation of the health an... more Heart rate variability (HRV) has become a wide-spread area for the investigation of the health and stress states of individuals. This paper aims at exploring the effectiveness of representing HRV measures with alternative modalities, other than visual displays, such as audio or haptics. Therefore, we undertook a preliminary study in which we applied a parameter mapping sonification approach to transform the HRV signal into an audible form. In this work, we sought to evaluate the human perception of the developed auditory interface. Hence, a dataset that involves interbeat interval measurements of individuals experiencing changes in mental state in the form of meditation was selected as the basis of the study. The HRV parameters of the dataset were mapped to acoustic features using a linear mapping technique. The feasibility of the system was assessed by measuring the learnability, performance, latency, and confidence aspects. The results suggest a great potential of incorporating au...
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Papers by Mariam Bahameish