Pablo Paredes - Academia.edu (original) (raw)
Papers by Pablo Paredes
BACKGROUND Stress is a risk factor associated with physiological and mental health problems. Unob... more BACKGROUND Stress is a risk factor associated with physiological and mental health problems. Unobtrusive, continuous stress sensing would enable precision health monitoring and proactive interventions, but current sensing methods are often inconvenient, expensive, or suffer from limited adherence. Prior work has shown the possibility to detect acute stress using biomechanical models derived from passive logging of computer input devices. OBJECTIVE Our objective is to detect acute stress from passive movement measurements of everyday interactions on a laptop trackpad: (1) click, (2) steer, and (3) drag and drop. METHODS We built upon previous work, detecting acute stress through the biomechanical analyses of canonical computer mouse interactions and extended it to study similar interactions with the trackpad. A total of 18 participants carried out 40 trials each of three different types of movement—(1) click, (2) steer, and (3) drag and drop—under both relaxed and stressed conditions...
Companion of the 2021 ACM/IEEE International Conference on Human-Robot Interaction
Figure 1: A user stands-up as he follows the autonomously rising desk from their ergonomic sittin... more Figure 1: A user stands-up as he follows the autonomously rising desk from their ergonomic sitting desk height (left) to their ergonomic standing desk height in (right)
The COVID-19 pandemic continues to affect work life and the mental health burden globally. Asking... more The COVID-19 pandemic continues to affect work life and the mental health burden globally. Asking millions of workers to work from home or go back to work with the risk of being infected is a problematic aspect of the pandemic increasing stress and negatively impacting productivity. The objective of occupational and precision health research and practice is to precisely measure and sustain workers' mental health and productivity. Best practices for the workplace propose the need to identify the early effects of factors such as psychological distress and develop interventions for the proactive treatment of pre-disease stages of mental disorders. In this position paper, we propose the development of a novel platform for workers that integrates continuous sensing and long-term self-regulation interventions. The Stanford Wellbeing and Emotional Education Technology Platform (SWEET) is a digital wellbeing and occupational health platform designed as a compendium of ubiquitous technology modules to help manage stress and productivity, during and post-pandemic, while amplifying research on occupational precision mental health. Here, we discuss adapting our system in the wake of COVID-19.
Stress causes and exacerbates many physiological and men-tal health problems. Routine and unobtru... more Stress causes and exacerbates many physiological and men-tal health problems. Routine and unobtrusive monitoring of stress would enable a variety of treatments, from break-taking to calming exercises. It may also be a valuable tool for as-sessing effects (frustration, difficulty) of using interfaces or applications. Custom sensing hardware is a poor option, be-cause of the need to buy/wear/use it continuously, even before stress-related problems are evident. Here we explore stress measurement from common computer mouse operations. We use a simple model of arm-hand dynamics that captures mus-cle stiffness during mouse movement. We show that the within-subject mouse-derived stress measure is quite strong, even compared to concurrent physiological sensor measure-ments. While our study used fixed mouse tasks, the stress sig-nal was still strong even when averaged across widely varying task geometries. We argue that mouse sensing “in the wild” may be feasible, by analyzing frequently-per...
Increasing levels of work-related stress are pervasive among US workers leading to decreased well... more Increasing levels of work-related stress are pervasive among US workers leading to decreased wellbeing, lower productivity, and poor long-term health outcomes. Controlled breathing exercises can be an effective way of managing stress. However, they often require focused attention from the user, distracting them from their tasks. In this workshop paper, we present Breathing Edges—a browser plugin designed to help mitigate stress. The plugin attempts to turn the browser into an entrainment tool (i.e., a tool able to alter physiology via indirect stimulus without conscious participation from the user) by injecting a dynamic color gradient animation into the periphery of the active browsing window that emulates rhythmic breathing toward helping users maintain a calm state. Through an exploratory, mixed-methods study (N=16) we investigate performance changes, distraction, and usability during two reading comprehension tasks. Results highlight the potential of this approach and we discuss...
Copyright held by the owner/author(s). Workshop 33: Conversational Agents for Health and Wellbein... more Copyright held by the owner/author(s). Workshop 33: Conversational Agents for Health and Wellbeing CHI’20, April 25–30, 2020, Honolulu, HI, USA Abstract Mobile users are increasingly using chatbots to access services. Chatbots that understand user problems and emotions could be effective public health tools for stress management for those without professional support. However, stress management applications (including chatbots) have thus far been met with low adoption and high abandonment. In this workshop paper, we explore if short interactions with multiple chatbots can have wellness benefits and propose the creation of a suite of shallow chatbots—called Popbots—aimed at providing in-situ support for daily stressors by being quick, readily available, and engaging. To evaluate the feasibility of our approach and gather preliminary user feedback, we conducted an exploratory Wizard of Oz study (N=14), developed a prototype system, and evaluated this prototype in an online pilot (N=14...
arXiv: Signal Processing, 2020
Prior work demonstrated the potential of using Linear Predictive Coding (LPC) to approximate musc... more Prior work demonstrated the potential of using Linear Predictive Coding (LPC) to approximate muscle stiffness and damping from computer mouse (a.k.a. mouse) movement to predict stress levels of users. Theoretically, muscle stiffness in the arm can be estimated using a mass-spring-damper (MSD) biomechanical model of the arm. However, the damping frequency and damping ratio values derived using LPC have not yet been compared with those from the theoretical MSD model. In this work, we demonstrate the damping frequency and damping ratio from LPC are significantly correlated with those from MSD model, thus confirming the validity of using LPC to infer muscle stiffness and damping. We also compare the stress level binary classification performance using the values from LPC and MSD with each other and with neural network-based baselines. We found comparable performance across all conditions demonstrating the efficacy of LPC and MSD model-based stress prediction.
In this paper we describe the formatting requirements for SIGCHI Conference Proceedings, and offe... more In this paper we describe the formatting requirements for SIGCHI Conference Proceedings, and offer recommendations on writing for the worldwide SIGCHI readership. Please review this document even if you have submitted to SIGCHI conferences before, for some format details have changed relative to previous years. These include the formatting of table captions, the formatting of references, and a requirement to include ACM DL indexing information. Author
The average commute time in the US is close to 30 minutes each way. In a world where we wouldn’t ... more The average commute time in the US is close to 30 minutes each way. In a world where we wouldn’t need to “drive” the car while commuting, what would be the best use of this time? We see autonomous vehicles as an opportunity to help people reach wellness and high productivity levels. After all, commute time is not just moving from point A to point B. It is also about moving from a mindset to another. For example, from a family/relaxed mentality to a worker/productive mentality and vice-versa. We propose to use many sensors and multi-sensory feedback to personalize the in-car experience. We propose three types of interventions: in-car movement-based mindfulness, interactive storytelling for drivers, immersive environments for users of autonomous vehicles. We close with a discussion of the way to link values and mindsets to a “healthy” commute. Author
Chronic Stress
Depression and anxiety disrupt daily function and their effects can be long-lasting and devastati... more Depression and anxiety disrupt daily function and their effects can be long-lasting and devastating, yet there are no established physiological indicators that can be used to predict onset, diagnose, or target treatments. In this review, we conceptualize depression and anxiety as maladaptive responses to repetitive stress. We provide an overview of the role of chronic stress in depression and anxiety and a review of current knowledge on objective stress indicators of depression and anxiety. We focused on cortisol, heart rate variability and skin conductance that have been well studied in depression and anxiety and implicated in clinical emotional states. A targeted PubMed search was undertaken prioritizing meta-analyses that have linked depression and anxiety to cortisol, heart rate variability and skin conductance. Consistent findings include reduced heart rate variability across depression and anxiety, reduced tonic and phasic skin conductance in depression, and elevated cortisol ...
Scientific Reports
In-car passive stress sensing could enable the monitoring of stress biomarkers while driving and ... more In-car passive stress sensing could enable the monitoring of stress biomarkers while driving and reach millions of commuters daily (i.e., 123 million daily commuters in the US alone). Here, we present a nonintrusive method to detect stress solely from steering angle data of a regular car. The method uses inverse filtering to convert angular movement data into a biomechanical Mass Spring Damper model of the arm and extracts its damped natural frequency as an approximation of muscle stiffness, which in turn reflects stress. We ran a within-subject study (N = 22), in which commuters drove a vehicle around a closed circuit in both stress and calm conditions. As hypothesized, cohort analysis revealed a significantly higher damped natural frequency for the stress condition (P = .023, d = 0.723). Subsequent automation of the method achieved rapid (i.e., within 8 turns) stress detection in the individual with a detection accuracy of 77%.
Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems
BACKGROUND Approximately 60%-80% of the primary care visits have a psychological stress component... more BACKGROUND Approximately 60%-80% of the primary care visits have a psychological stress component, but only 3% of patients receive stress management advice during these visits. Given recent advances in natural language processing, there is renewed interest in mental health chatbots. Conversational agents that can understand a user’s problems and deliver advice that mitigates the effects of daily stress could be an effective public health tool. However, such systems are complex to build and costly to develop. OBJECTIVE To address these challenges, our aim is to develop and evaluate a fully automated mobile suite of shallow chatbots—we call them Popbots—that may serve as a new species of chatbots and further complement human assistance in an ecosystem of stress management support. METHODS After conducting an exploratory Wizard of Oz study (N=14) to evaluate the feasibility of a suite of multiple chatbots, we conducted a web-based study (N=47) to evaluate the implementation of our prot...
BACKGROUND The daily commute could be a right moment to teach drivers to use movement or breath t... more BACKGROUND The daily commute could be a right moment to teach drivers to use movement or breath towards improving their mental health. Long commutes, the relevance of transitioning from home to work, and vice versa and the privacy of commuting by car make the commute an ideal scenario and time to perform mindful exercises safely. Whereas driving safety is paramount, mindful exercises might help commuters decrease their daily stress while staying alert. Increasing vehicle automation may present new opportunities but also new challenges. OBJECTIVE This study aimed to explore the design space for movement-based mindful interventions for commuters. We used qualitative analysis of simulated driving experiences in combination with simple movements to obtain key design insights. METHODS We performed a semistructured viability assessment in 2 parts. First, a think-aloud technique was used to obtain information about a driving task. Drivers (N=12) were given simple instructions to complete m...
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2018
We present the use of in-car virtual reality (VR) as a way to create calm, mindful experiences fo... more We present the use of in-car virtual reality (VR) as a way to create calm, mindful experiences for passengers and, someday, autonomous vehicle occupants. Specifically, we describe a series of studies aimed at exploring appropriate VR content, understanding the influence of car movement, and determining the length and other parameters of the simulation to avoid physical discomfort. Overall, our quantitative and qualitative insights suggest calm VR applications are well suited to an automotive context. Testing combinations of VR content designed to provide the participant with a static or dynamic experience versus stationary and moving vehicle modes, we find that a simulated experience of diving in the ocean while in a moving car elicited significantly lower levels of autonomic arousal as compared with a static VR plus stationary car condition. No significant motion sickness effects were subjectively reported by participants nor observable in the data, though a crossover interaction e...
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2018
Motivated by the idea that slow breathing practices could transform the automobile commute from a... more Motivated by the idea that slow breathing practices could transform the automobile commute from a depleting, mindless activity into a calming, mindful experience, we introduce the first guided slow breathing intervention for drivers. We describe a controlled in-lab experiment (N=24) that contrasts the effectiveness and impact of haptic and voice guidance modalities at slowing drivers' breathing pace, which is a known modulator of stress. The experiment was conducted in two simulated driving environments (city, highway) while driving in one of two driving modes (autonomous, manual). Results show that both haptic and voice guidance systems can reduce drivers' breathing rate and provide a sustained post-intervention effect without affecting driving safety. Subjectively, most participants (19/24) preferred the haptic stimuli as they found it more natural to follow, less distracting, and easier to engage and disengage from, compared to the voice stimuli. Finally, while most parti...
Proceedings of the 12th EAI International Conference on Pervasive Computing Technologies for Healthcare, 2018
In this paper, we explore the delivery of fast breathing interventions in a driving context, give... more In this paper, we explore the delivery of fast breathing interventions in a driving context, given the proven effects of high-paced breathing on autonomic arousal. Through in-lab simulator studies, we demonstrate the feasibility of using haptic guidance to increase breathing rate, intensity, and heart rate as well as subjective perceptions of alertness and focus. We also assess usability and user receptivity towards the approach across various simulated driving scenarios (highway, city), times of day (day, night), and traffic levels (low, heavy, fast). In doing so, we outline specific use cases where fast breathing interventions are more or less appropriate and beneficial (e.g., during long, monotonous drives on the highway or at night vs. complex or tense driving scenarios), and we offer fertile future directions for the continued development of breathing systems for health and well-being.
Journal of medical Internet research, Jan 4, 2017
The daily commute could be a right moment to teach drivers to use movement or breath towards impr... more The daily commute could be a right moment to teach drivers to use movement or breath towards improving their mental health. Long commutes, the relevance of transitioning from home to work, and vice versa and the privacy of commuting by car make the commute an ideal scenario and time to perform mindful exercises safely. Whereas driving safety is paramount, mindful exercises might help commuters decrease their daily stress while staying alert. Increasing vehicle automation may present new opportunities but also new challenges. This study aimed to explore the design space for movement-based mindful interventions for commuters. We used qualitative analysis of simulated driving experiences in combination with simple movements to obtain key design insights. We performed a semistructured viability assessment in 2 parts. First, a think-aloud technique was used to obtain information about a driving task. Drivers (N=12) were given simple instructions to complete movements (configural or breat...
Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing, 2017
BACKGROUND Stress is a risk factor associated with physiological and mental health problems. Unob... more BACKGROUND Stress is a risk factor associated with physiological and mental health problems. Unobtrusive, continuous stress sensing would enable precision health monitoring and proactive interventions, but current sensing methods are often inconvenient, expensive, or suffer from limited adherence. Prior work has shown the possibility to detect acute stress using biomechanical models derived from passive logging of computer input devices. OBJECTIVE Our objective is to detect acute stress from passive movement measurements of everyday interactions on a laptop trackpad: (1) click, (2) steer, and (3) drag and drop. METHODS We built upon previous work, detecting acute stress through the biomechanical analyses of canonical computer mouse interactions and extended it to study similar interactions with the trackpad. A total of 18 participants carried out 40 trials each of three different types of movement—(1) click, (2) steer, and (3) drag and drop—under both relaxed and stressed conditions...
Companion of the 2021 ACM/IEEE International Conference on Human-Robot Interaction
Figure 1: A user stands-up as he follows the autonomously rising desk from their ergonomic sittin... more Figure 1: A user stands-up as he follows the autonomously rising desk from their ergonomic sitting desk height (left) to their ergonomic standing desk height in (right)
The COVID-19 pandemic continues to affect work life and the mental health burden globally. Asking... more The COVID-19 pandemic continues to affect work life and the mental health burden globally. Asking millions of workers to work from home or go back to work with the risk of being infected is a problematic aspect of the pandemic increasing stress and negatively impacting productivity. The objective of occupational and precision health research and practice is to precisely measure and sustain workers' mental health and productivity. Best practices for the workplace propose the need to identify the early effects of factors such as psychological distress and develop interventions for the proactive treatment of pre-disease stages of mental disorders. In this position paper, we propose the development of a novel platform for workers that integrates continuous sensing and long-term self-regulation interventions. The Stanford Wellbeing and Emotional Education Technology Platform (SWEET) is a digital wellbeing and occupational health platform designed as a compendium of ubiquitous technology modules to help manage stress and productivity, during and post-pandemic, while amplifying research on occupational precision mental health. Here, we discuss adapting our system in the wake of COVID-19.
Stress causes and exacerbates many physiological and men-tal health problems. Routine and unobtru... more Stress causes and exacerbates many physiological and men-tal health problems. Routine and unobtrusive monitoring of stress would enable a variety of treatments, from break-taking to calming exercises. It may also be a valuable tool for as-sessing effects (frustration, difficulty) of using interfaces or applications. Custom sensing hardware is a poor option, be-cause of the need to buy/wear/use it continuously, even before stress-related problems are evident. Here we explore stress measurement from common computer mouse operations. We use a simple model of arm-hand dynamics that captures mus-cle stiffness during mouse movement. We show that the within-subject mouse-derived stress measure is quite strong, even compared to concurrent physiological sensor measure-ments. While our study used fixed mouse tasks, the stress sig-nal was still strong even when averaged across widely varying task geometries. We argue that mouse sensing “in the wild” may be feasible, by analyzing frequently-per...
Increasing levels of work-related stress are pervasive among US workers leading to decreased well... more Increasing levels of work-related stress are pervasive among US workers leading to decreased wellbeing, lower productivity, and poor long-term health outcomes. Controlled breathing exercises can be an effective way of managing stress. However, they often require focused attention from the user, distracting them from their tasks. In this workshop paper, we present Breathing Edges—a browser plugin designed to help mitigate stress. The plugin attempts to turn the browser into an entrainment tool (i.e., a tool able to alter physiology via indirect stimulus without conscious participation from the user) by injecting a dynamic color gradient animation into the periphery of the active browsing window that emulates rhythmic breathing toward helping users maintain a calm state. Through an exploratory, mixed-methods study (N=16) we investigate performance changes, distraction, and usability during two reading comprehension tasks. Results highlight the potential of this approach and we discuss...
Copyright held by the owner/author(s). Workshop 33: Conversational Agents for Health and Wellbein... more Copyright held by the owner/author(s). Workshop 33: Conversational Agents for Health and Wellbeing CHI’20, April 25–30, 2020, Honolulu, HI, USA Abstract Mobile users are increasingly using chatbots to access services. Chatbots that understand user problems and emotions could be effective public health tools for stress management for those without professional support. However, stress management applications (including chatbots) have thus far been met with low adoption and high abandonment. In this workshop paper, we explore if short interactions with multiple chatbots can have wellness benefits and propose the creation of a suite of shallow chatbots—called Popbots—aimed at providing in-situ support for daily stressors by being quick, readily available, and engaging. To evaluate the feasibility of our approach and gather preliminary user feedback, we conducted an exploratory Wizard of Oz study (N=14), developed a prototype system, and evaluated this prototype in an online pilot (N=14...
arXiv: Signal Processing, 2020
Prior work demonstrated the potential of using Linear Predictive Coding (LPC) to approximate musc... more Prior work demonstrated the potential of using Linear Predictive Coding (LPC) to approximate muscle stiffness and damping from computer mouse (a.k.a. mouse) movement to predict stress levels of users. Theoretically, muscle stiffness in the arm can be estimated using a mass-spring-damper (MSD) biomechanical model of the arm. However, the damping frequency and damping ratio values derived using LPC have not yet been compared with those from the theoretical MSD model. In this work, we demonstrate the damping frequency and damping ratio from LPC are significantly correlated with those from MSD model, thus confirming the validity of using LPC to infer muscle stiffness and damping. We also compare the stress level binary classification performance using the values from LPC and MSD with each other and with neural network-based baselines. We found comparable performance across all conditions demonstrating the efficacy of LPC and MSD model-based stress prediction.
In this paper we describe the formatting requirements for SIGCHI Conference Proceedings, and offe... more In this paper we describe the formatting requirements for SIGCHI Conference Proceedings, and offer recommendations on writing for the worldwide SIGCHI readership. Please review this document even if you have submitted to SIGCHI conferences before, for some format details have changed relative to previous years. These include the formatting of table captions, the formatting of references, and a requirement to include ACM DL indexing information. Author
The average commute time in the US is close to 30 minutes each way. In a world where we wouldn’t ... more The average commute time in the US is close to 30 minutes each way. In a world where we wouldn’t need to “drive” the car while commuting, what would be the best use of this time? We see autonomous vehicles as an opportunity to help people reach wellness and high productivity levels. After all, commute time is not just moving from point A to point B. It is also about moving from a mindset to another. For example, from a family/relaxed mentality to a worker/productive mentality and vice-versa. We propose to use many sensors and multi-sensory feedback to personalize the in-car experience. We propose three types of interventions: in-car movement-based mindfulness, interactive storytelling for drivers, immersive environments for users of autonomous vehicles. We close with a discussion of the way to link values and mindsets to a “healthy” commute. Author
Chronic Stress
Depression and anxiety disrupt daily function and their effects can be long-lasting and devastati... more Depression and anxiety disrupt daily function and their effects can be long-lasting and devastating, yet there are no established physiological indicators that can be used to predict onset, diagnose, or target treatments. In this review, we conceptualize depression and anxiety as maladaptive responses to repetitive stress. We provide an overview of the role of chronic stress in depression and anxiety and a review of current knowledge on objective stress indicators of depression and anxiety. We focused on cortisol, heart rate variability and skin conductance that have been well studied in depression and anxiety and implicated in clinical emotional states. A targeted PubMed search was undertaken prioritizing meta-analyses that have linked depression and anxiety to cortisol, heart rate variability and skin conductance. Consistent findings include reduced heart rate variability across depression and anxiety, reduced tonic and phasic skin conductance in depression, and elevated cortisol ...
Scientific Reports
In-car passive stress sensing could enable the monitoring of stress biomarkers while driving and ... more In-car passive stress sensing could enable the monitoring of stress biomarkers while driving and reach millions of commuters daily (i.e., 123 million daily commuters in the US alone). Here, we present a nonintrusive method to detect stress solely from steering angle data of a regular car. The method uses inverse filtering to convert angular movement data into a biomechanical Mass Spring Damper model of the arm and extracts its damped natural frequency as an approximation of muscle stiffness, which in turn reflects stress. We ran a within-subject study (N = 22), in which commuters drove a vehicle around a closed circuit in both stress and calm conditions. As hypothesized, cohort analysis revealed a significantly higher damped natural frequency for the stress condition (P = .023, d = 0.723). Subsequent automation of the method achieved rapid (i.e., within 8 turns) stress detection in the individual with a detection accuracy of 77%.
Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems
BACKGROUND Approximately 60%-80% of the primary care visits have a psychological stress component... more BACKGROUND Approximately 60%-80% of the primary care visits have a psychological stress component, but only 3% of patients receive stress management advice during these visits. Given recent advances in natural language processing, there is renewed interest in mental health chatbots. Conversational agents that can understand a user’s problems and deliver advice that mitigates the effects of daily stress could be an effective public health tool. However, such systems are complex to build and costly to develop. OBJECTIVE To address these challenges, our aim is to develop and evaluate a fully automated mobile suite of shallow chatbots—we call them Popbots—that may serve as a new species of chatbots and further complement human assistance in an ecosystem of stress management support. METHODS After conducting an exploratory Wizard of Oz study (N=14) to evaluate the feasibility of a suite of multiple chatbots, we conducted a web-based study (N=47) to evaluate the implementation of our prot...
BACKGROUND The daily commute could be a right moment to teach drivers to use movement or breath t... more BACKGROUND The daily commute could be a right moment to teach drivers to use movement or breath towards improving their mental health. Long commutes, the relevance of transitioning from home to work, and vice versa and the privacy of commuting by car make the commute an ideal scenario and time to perform mindful exercises safely. Whereas driving safety is paramount, mindful exercises might help commuters decrease their daily stress while staying alert. Increasing vehicle automation may present new opportunities but also new challenges. OBJECTIVE This study aimed to explore the design space for movement-based mindful interventions for commuters. We used qualitative analysis of simulated driving experiences in combination with simple movements to obtain key design insights. METHODS We performed a semistructured viability assessment in 2 parts. First, a think-aloud technique was used to obtain information about a driving task. Drivers (N=12) were given simple instructions to complete m...
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2018
We present the use of in-car virtual reality (VR) as a way to create calm, mindful experiences fo... more We present the use of in-car virtual reality (VR) as a way to create calm, mindful experiences for passengers and, someday, autonomous vehicle occupants. Specifically, we describe a series of studies aimed at exploring appropriate VR content, understanding the influence of car movement, and determining the length and other parameters of the simulation to avoid physical discomfort. Overall, our quantitative and qualitative insights suggest calm VR applications are well suited to an automotive context. Testing combinations of VR content designed to provide the participant with a static or dynamic experience versus stationary and moving vehicle modes, we find that a simulated experience of diving in the ocean while in a moving car elicited significantly lower levels of autonomic arousal as compared with a static VR plus stationary car condition. No significant motion sickness effects were subjectively reported by participants nor observable in the data, though a crossover interaction e...
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2018
Motivated by the idea that slow breathing practices could transform the automobile commute from a... more Motivated by the idea that slow breathing practices could transform the automobile commute from a depleting, mindless activity into a calming, mindful experience, we introduce the first guided slow breathing intervention for drivers. We describe a controlled in-lab experiment (N=24) that contrasts the effectiveness and impact of haptic and voice guidance modalities at slowing drivers' breathing pace, which is a known modulator of stress. The experiment was conducted in two simulated driving environments (city, highway) while driving in one of two driving modes (autonomous, manual). Results show that both haptic and voice guidance systems can reduce drivers' breathing rate and provide a sustained post-intervention effect without affecting driving safety. Subjectively, most participants (19/24) preferred the haptic stimuli as they found it more natural to follow, less distracting, and easier to engage and disengage from, compared to the voice stimuli. Finally, while most parti...
Proceedings of the 12th EAI International Conference on Pervasive Computing Technologies for Healthcare, 2018
In this paper, we explore the delivery of fast breathing interventions in a driving context, give... more In this paper, we explore the delivery of fast breathing interventions in a driving context, given the proven effects of high-paced breathing on autonomic arousal. Through in-lab simulator studies, we demonstrate the feasibility of using haptic guidance to increase breathing rate, intensity, and heart rate as well as subjective perceptions of alertness and focus. We also assess usability and user receptivity towards the approach across various simulated driving scenarios (highway, city), times of day (day, night), and traffic levels (low, heavy, fast). In doing so, we outline specific use cases where fast breathing interventions are more or less appropriate and beneficial (e.g., during long, monotonous drives on the highway or at night vs. complex or tense driving scenarios), and we offer fertile future directions for the continued development of breathing systems for health and well-being.
Journal of medical Internet research, Jan 4, 2017
The daily commute could be a right moment to teach drivers to use movement or breath towards impr... more The daily commute could be a right moment to teach drivers to use movement or breath towards improving their mental health. Long commutes, the relevance of transitioning from home to work, and vice versa and the privacy of commuting by car make the commute an ideal scenario and time to perform mindful exercises safely. Whereas driving safety is paramount, mindful exercises might help commuters decrease their daily stress while staying alert. Increasing vehicle automation may present new opportunities but also new challenges. This study aimed to explore the design space for movement-based mindful interventions for commuters. We used qualitative analysis of simulated driving experiences in combination with simple movements to obtain key design insights. We performed a semistructured viability assessment in 2 parts. First, a think-aloud technique was used to obtain information about a driving task. Drivers (N=12) were given simple instructions to complete movements (configural or breat...
Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing, 2017