Research
Research is integral to the Personal Health Informatics doctoral degree, as students and faculty work together to find impactful solutions to today’s health and wellness challenges. The transition from centralized, provider-centric treatment to personalized, patient-focused care requires researchers to cross the boundaries of public health, medicine, and social and computer sciences. which in turn prepares students for excellence in a specific research area of personal health informatics. It is this interdisciplinary experience that sets the program apart.
Research is integral to the Personal Health Informatics doctoral degree, as students and faculty work together to find impactful solutions to today’s health and wellness challenges. The transition from centralized, provider-centric treatment to personalized, patient-focused care requires researchers to cross the boundaries of public health, medicine, and social and computer sciences. which in turn prepares students for excellence in a specific research area of personal health informatics. It is this interdisciplinary experience that sets the program apart.
Research is integral to the Personal Health Informatics doctoral degree, as students and faculty work together to find impactful solutions to today’s health and wellness challenges. The transition from centralized, provider-centric treatment to personalized, patient-focused care requires researchers to cross the boundaries of public health, medicine, and social and computer sciences. which in turn prepares students for excellence in a specific research area of personal health informatics. It is this interdisciplinary experience that sets the program apart.
Research is integral to the Personal Health Informatics doctoral degree, as students and faculty work together to find impactful solutions to today’s health and wellness challenges. The transition from centralized, provider-centric treatment to personalized, patient-focused care requires researchers to cross the boundaries of public health, medicine, and social and computer sciences. which in turn prepares students for excellence in a specific research area of personal health informatics. It is this interdisciplinary experience that sets the program apart.
Research is integral to the Personal Health Informatics doctoral degree, as students and faculty work together to find impactful solutions to today’s health and wellness challenges. The transition from centralized, provider-centric treatment to personalized, patient-focused care requires researchers to cross the boundaries of public health, medicine, and social and computer sciences. which in turn prepares students for excellence in a specific research area of personal health informatics. It is this interdisciplinary experience that sets the program apart.
Research is integral to the Personal Health Informatics doctoral degree, as students and faculty work together to find impactful solutions to today’s health and wellness challenges. The transition from centralized, provider-centric treatment to personalized, patient-focused care requires researchers to cross the boundaries of public health, medicine, and social and computer sciences. which in turn prepares students for excellence in a specific research area of personal health informatics. It is this interdisciplinary experience that sets the program apart.
Research is integral to the Personal Health Informatics doctoral degree, as students and faculty work together to find impactful solutions to today’s health and wellness challenges. The transition from centralized, provider-centric treatment to personalized, patient-focused care requires researchers to cross the boundaries of public health, medicine, and social and computer sciences. which in turn prepares students for excellence in a specific research area of personal health informatics. It is this interdisciplinary experience that sets the program apart.
Leverages behavioral informatics to develop affordable, technology-based healthcare solutions.
Leverages behavioral informatics to develop affordable, technology-based healthcare solutions.
Invents and validates systems, methodologies, and algorithms for new mobile health applications.
Invents and validates systems, methodologies, and algorithms for new mobile health applications.
Designs conversational agents for healthcare, such as simulating face-to-face counseling.
Designs conversational agents for healthcare, such as simulating face-to-face counseling.
Develops nursing research expertise and effective technology interventions for at-risk adults.
Develops nursing research expertise and effective technology interventions for at-risk adults.
Works on developing data-driven solutions to enable effective sensing and interventions for mental- and behavioral-health outcomes with mobile and ubiquitous technologies.
Works on developing data-driven solutions to enable effective sensing and interventions for mental- and behavioral-health outcomes with mobile and ubiquitous technologies.
The ACT Lab performs research in medical making, design tools for non-engineers, and design tool for automatic machine knitting.
The ACT Lab performs research in medical making, design tools for non-engineers, and design tool for automatic machine knitting.
Explores visualization for human perception and vision, visual encodings, design thinking, and more.
Explores visualization for human perception and vision, visual encodings, design thinking, and more.
Conducts interdisciplinary work on speech communication and human-computer interaction.
Conducts interdisciplinary work on speech communication and human-computer interaction.
Studies the interplay between sucking, feeding, and early infant vocal development in full-term, premature, and other infant populations such as infants with cleft lip and palate.
Studies the interplay between sucking, feeding, and early infant vocal development in full-term, premature, and other infant populations such as infants with cleft lip and palate.
Leverages behavioral informatics to develop affordable, technology-based healthcare solutions.
Leverages behavioral informatics to develop affordable, technology-based healthcare solutions.
Invents and validates systems, methodologies, and algorithms for new mobile health applications.
Invents and validates systems, methodologies, and algorithms for new mobile health applications.
Designs conversational agents for healthcare, such as simulating face-to-face counseling.
Designs conversational agents for healthcare, such as simulating face-to-face counseling.
Develops nursing research expertise and effective technology interventions for at-risk adults.
Develops nursing research expertise and effective technology interventions for at-risk adults.
Works on developing data-driven solutions to enable effective sensing and interventions for mental- and behavioral-health outcomes with mobile and ubiquitous technologies.
Works on developing data-driven solutions to enable effective sensing and interventions for mental- and behavioral-health outcomes with mobile and ubiquitous technologies.
The ACT Lab performs research in medical making, design tools for non-engineers, and design tool for automatic machine knitting.
The ACT Lab performs research in medical making, design tools for non-engineers, and design tool for automatic machine knitting.
Explores visualization for human perception and vision, visual encodings, design thinking, and more.
Explores visualization for human perception and vision, visual encodings, design thinking, and more.
Conducts interdisciplinary work on speech communication and human-computer interaction.
Conducts interdisciplinary work on speech communication and human-computer interaction.
Studies the interplay between sucking, feeding, and early infant vocal development in full-term, premature, and other infant populations such as infants with cleft lip and palate.
Studies the interplay between sucking, feeding, and early infant vocal development in full-term, premature, and other infant populations such as infants with cleft lip and palate.
Leverages behavioral informatics to develop affordable, technology-based healthcare solutions.
Invents and validates systems, methodologies, and algorithms for new mobile health applications.
Designs conversational agents for healthcare, such as simulating face-to-face counseling.
Develops nursing research expertise and effective technology interventions for at-risk adults.
Works on developing data-driven solutions to enable effective sensing and interventions for mental- and behavioral-health outcomes with mobile and ubiquitous technologies.
The ACT Lab performs research in medical making, design tools for non-engineers, and design tool for automatic machine knitting.
Explores visualization for human perception and vision, visual encodings, design thinking, and more.
Conducts interdisciplinary work on speech communication and human-computer interaction.
Studies the interplay between sucking, feeding, and early infant vocal development in full-term, premature, and other infant populations such as infants with cleft lip and palate.
Leverages behavioral informatics to develop affordable, technology-based healthcare solutions.
Leverages behavioral informatics to develop affordable, technology-based healthcare solutions.
Invents and validates systems, methodologies, and algorithms for new mobile health applications.
Invents and validates systems, methodologies, and algorithms for new mobile health applications.
Designs conversational agents for healthcare, such as simulating face-to-face counseling.
Designs conversational agents for healthcare, such as simulating face-to-face counseling.
Develops nursing research expertise and effective technology interventions for at-risk adults.
Develops nursing research expertise and effective technology interventions for at-risk adults.
Works on developing data-driven solutions to enable effective sensing and interventions for mental- and behavioral-health outcomes with mobile and ubiquitous technologies.
Works on developing data-driven solutions to enable effective sensing and interventions for mental- and behavioral-health outcomes with mobile and ubiquitous technologies.
The ACT Lab performs research in medical making, design tools for non-engineers, and design tool for automatic machine knitting.
The ACT Lab performs research in medical making, design tools for non-engineers, and design tool for automatic machine knitting.
Explores visualization for human perception and vision, visual encodings, design thinking, and more.
Explores visualization for human perception and vision, visual encodings, design thinking, and more.
Conducts interdisciplinary work on speech communication and human-computer interaction.
Conducts interdisciplinary work on speech communication and human-computer interaction.
Studies the interplay between sucking, feeding, and early infant vocal development in full-term, premature, and other infant populations such as infants with cleft lip and palate.
Studies the interplay between sucking, feeding, and early infant vocal development in full-term, premature, and other infant populations such as infants with cleft lip and palate.
Leverages behavioral informatics to develop affordable, technology-based healthcare solutions.
Leverages behavioral informatics to develop affordable, technology-based healthcare solutions.
Invents and validates systems, methodologies, and algorithms for new mobile health applications.
Invents and validates systems, methodologies, and algorithms for new mobile health applications.
Designs conversational agents for healthcare, such as simulating face-to-face counseling.
Designs conversational agents for healthcare, such as simulating face-to-face counseling.
Develops nursing research expertise and effective technology interventions for at-risk adults.
Develops nursing research expertise and effective technology interventions for at-risk adults.
Works on developing data-driven solutions to enable effective sensing and interventions for mental- and behavioral-health outcomes with mobile and ubiquitous technologies.
Works on developing data-driven solutions to enable effective sensing and interventions for mental- and behavioral-health outcomes with mobile and ubiquitous technologies.
The ACT Lab performs research in medical making, design tools for non-engineers, and design tool for automatic machine knitting.
The ACT Lab performs research in medical making, design tools for non-engineers, and design tool for automatic machine knitting.
Explores visualization for human perception and vision, visual encodings, design thinking, and more.
Explores visualization for human perception and vision, visual encodings, design thinking, and more.
Conducts interdisciplinary work on speech communication and human-computer interaction.
Conducts interdisciplinary work on speech communication and human-computer interaction.
Studies the interplay between sucking, feeding, and early infant vocal development in full-term, premature, and other infant populations such as infants with cleft lip and palate.
Studies the interplay between sucking, feeding, and early infant vocal development in full-term, premature, and other infant populations such as infants with cleft lip and palate.
Although physical activity reduces the risk of chronic and mental health issues, low-income and racially marginalized communities are unable to exercise regularly because of systemic discrimination that constrains their ability to exercise. Our Storywell smartphone app demonstrated that community storytelling on fitness tracking data can support physical activity in marginalized communities. To further innovate in digital health storytelling, we are examining how just-in-time exercise storytelling from community members can further support physical activity.
Collaborators: Mattapan Food and Fitness Coalition
Supported by: Google
PHI Faculty: Matthew Goodwin
Stereotypical motor movements are one of the most common and least understood behaviors occurring in individuals with ASD. Stereotypical motor movements are complex and thought to serve a multiplicity of functions. While no one theory has obtained overwhelming support, there is evidence for biological, operant, and homeostatic interpretations.
Collaborator(s): MIT Media Lab, The Groden Center, Inc.
Supported by: Nancy Lurie Marks Family Foundation
PHI Faculty: Stephen Intille
This project is exploring how mobile technology can be used to support active commuting via bicycling, where individuals who would normally be commuting by car may instead commute via bicycle. They may do this because of a novel technological system that would create a car-free riding experience, dramatically enhancing comfort and safety.
PHI Faculty: Stephen Intille
Longitudinal sensor data collected passively from wearable activity monitors and mobile phones will transform behavioral science by allowing researchers to use “big data,” but at the person-level, to understand how behavior and related environmental exposures impact health outcomes and personalize health intervention and research. We propose to develop and test a system that permits typical mobile application game players to help scientists improve this type of data, by adding additional annotations that enrich the data, making it more useful for behavioral science and more amenable to automatic processing. This will help researchers to better understand how individual-level behaviors relate to health outcomes in current research studies that collect personal-level sensor data such as NHANES and the Women’s Health Study, and future big data ventures such as the new Precision Medicine Initiative.
Collaborators: Dinesh John (Northeastern University), Seth Cooper (Northeastern University)
Supported by: NIH
PHI Faculty: Timothy Bickmore
The purpose of this project is to develop a conversational agent system that counsels terminally ill patients in order to alleviate their suffering and improve their quality of life. Although many interventions have now been developed to address palliative care for specific chronic diseases, little has been done to address the overall quality of life for older adults with serious illness, spanning not only the functional aspects of symptom and medication management, but the affective aspects of suffering. In this project, we are developing a relational agent to counsel patients at home about medication adherence, stress management, advanced care planning, and spiritual support, and to provide referrals to palliative care services when needed.
Collaborators: Boston Medical Center
Supported by: NIH National Institute for Nursing Research
We are working with communities in a network of predominately African American churches in the Boston area, along with their Health Ministries and church leadership, to improve the overall health of church members. The intervention leverages a smartphone-based conversational agent that promotes physical activity, nutrition, healthy hydration, stress reduction through guided meditation, mental health care treatment, domestic violence awareness, and COVID and influenza vaccination.
Collaborators: Black Ministerial Alliance TenPoint of Boston, Dr. Michael Paasche-Orlow (Tufts Medical Center), Profs. Stephen Intille and Jessica Hoffman (Northeastern), Andrea Parker (Georgia Tech), Drs. Julien Dedier, Rebecca Perkins, and Natalie Joseph (Boston Medical Center).
Supported by: National Science Foundation and the NIH National Institute on Minority Health and Health Disparities
PHI Faculty: Cody Dunne, Stephen Intille
Type 1 diabetes (T1D), also called insulin dependent diabetes and juvenile diabetes, is an autoimmune disease which afflicts 1.25 million Americans. There are 40 thousand new diagnoses each year, and almost half of those are children and adolescents under age 20 years. The costs for our healthcare system are enormous, estimated at $14 billion annually. T1D is incurable, and people with T1D are estimated to lose over 10 years from their life expectancy. We are designing, building, and evaluating interactive visualization tools to help T1D patients and their caregivers make treatment decisions. In these visualizations we are showing data we collect using multiple devices and have data on the patient blood glucose levels, insulin administered, food eaten, exercise, and stress to name a few. Our tools are used by patients to understand the trends between scheduled events such as mealtimes, bedtimes, and overnight as well as irregular events like periods of exercise, stress, and illness. With this information, patients will be able to make more informed changes to their treatment protocols.
Collaborator: Boston Children’s Hospital
PHI Faculty: Timothy Bickmore
Most persons with spinal cord injury (SCI) require training and support for self-care management to help prevent the development of serious secondary conditions after hospital discharge. However, adherence to self-care management behaviors is poor once training with a therapist has ended. We have designed a virtual coach system, in which a relational agent engages individuals with SCI in simulated face-to-face conversations at home, to provide support and motivate adherence to self-care guidelines.
Collaborators: Boston University School of Public Health
Supported by: Nielsen Foundation
PHI Faculty: Stephen Intille
We are working on a variety of projects studying how to use mobile sensor data, especially from accelerometers, to detect physical activity (type, duration, and intensity), sedentary behavior, and sleep in adults and children.
Collaborator(s): EveryFit, Inc., Stanford Medical School
Supported by: NIH/NCI and NIH/NHLBI
Although physical activity reduces the risk of chronic and mental health issues, low-income and racially marginalized communities are unable to exercise regularly because of systemic discrimination that constrains their ability to exercise. Our Storywell smartphone app demonstrated that community storytelling on fitness tracking data can support physical activity in marginalized communities. To further innovate in digital health storytelling, we are examining how just-in-time exercise storytelling from community members can further support physical activity.
Collaborators: Mattapan Food and Fitness Coalition
Supported by: Google
PHI Faculty: Matthew Goodwin
Stereotypical motor movements are one of the most common and least understood behaviors occurring in individuals with ASD. Stereotypical motor movements are complex and thought to serve a multiplicity of functions. While no one theory has obtained overwhelming support, there is evidence for biological, operant, and homeostatic interpretations.
Collaborator(s): MIT Media Lab, The Groden Center, Inc.
Supported by: Nancy Lurie Marks Family Foundation
PHI Faculty: Stephen Intille
This project is exploring how mobile technology can be used to support active commuting via bicycling, where individuals who would normally be commuting by car may instead commute via bicycle. They may do this because of a novel technological system that would create a car-free riding experience, dramatically enhancing comfort and safety.
PHI Faculty: Stephen Intille
Longitudinal sensor data collected passively from wearable activity monitors and mobile phones will transform behavioral science by allowing researchers to use “big data,” but at the person-level, to understand how behavior and related environmental exposures impact health outcomes and personalize health intervention and research. We propose to develop and test a system that permits typical mobile application game players to help scientists improve this type of data, by adding additional annotations that enrich the data, making it more useful for behavioral science and more amenable to automatic processing. This will help researchers to better understand how individual-level behaviors relate to health outcomes in current research studies that collect personal-level sensor data such as NHANES and the Women’s Health Study, and future big data ventures such as the new Precision Medicine Initiative.
Collaborators: Dinesh John (Northeastern University), Seth Cooper (Northeastern University)
Supported by: NIH
PHI Faculty: Timothy Bickmore
The purpose of this project is to develop a conversational agent system that counsels terminally ill patients in order to alleviate their suffering and improve their quality of life. Although many interventions have now been developed to address palliative care for specific chronic diseases, little has been done to address the overall quality of life for older adults with serious illness, spanning not only the functional aspects of symptom and medication management, but the affective aspects of suffering. In this project, we are developing a relational agent to counsel patients at home about medication adherence, stress management, advanced care planning, and spiritual support, and to provide referrals to palliative care services when needed.
Collaborators: Boston Medical Center
Supported by: NIH National Institute for Nursing Research
We are working with communities in a network of predominately African American churches in the Boston area, along with their Health Ministries and church leadership, to improve the overall health of church members. The intervention leverages a smartphone-based conversational agent that promotes physical activity, nutrition, healthy hydration, stress reduction through guided meditation, mental health care treatment, domestic violence awareness, and COVID and influenza vaccination.
Collaborators: Black Ministerial Alliance TenPoint of Boston, Dr. Michael Paasche-Orlow (Tufts Medical Center), Profs. Stephen Intille and Jessica Hoffman (Northeastern), Andrea Parker (Georgia Tech), Drs. Julien Dedier, Rebecca Perkins, and Natalie Joseph (Boston Medical Center).
Supported by: National Science Foundation and the NIH National Institute on Minority Health and Health Disparities
PHI Faculty: Cody Dunne, Stephen Intille
Type 1 diabetes (T1D), also called insulin dependent diabetes and juvenile diabetes, is an autoimmune disease which afflicts 1.25 million Americans. There are 40 thousand new diagnoses each year, and almost half of those are children and adolescents under age 20 years. The costs for our healthcare system are enormous, estimated at $14 billion annually. T1D is incurable, and people with T1D are estimated to lose over 10 years from their life expectancy. We are designing, building, and evaluating interactive visualization tools to help T1D patients and their caregivers make treatment decisions. In these visualizations we are showing data we collect using multiple devices and have data on the patient blood glucose levels, insulin administered, food eaten, exercise, and stress to name a few. Our tools are used by patients to understand the trends between scheduled events such as mealtimes, bedtimes, and overnight as well as irregular events like periods of exercise, stress, and illness. With this information, patients will be able to make more informed changes to their treatment protocols.
Collaborator: Boston Children’s Hospital
PHI Faculty: Timothy Bickmore
Most persons with spinal cord injury (SCI) require training and support for self-care management to help prevent the development of serious secondary conditions after hospital discharge. However, adherence to self-care management behaviors is poor once training with a therapist has ended. We have designed a virtual coach system, in which a relational agent engages individuals with SCI in simulated face-to-face conversations at home, to provide support and motivate adherence to self-care guidelines.
Collaborators: Boston University School of Public Health
Supported by: Nielsen Foundation
PHI Faculty: Stephen Intille
We are working on a variety of projects studying how to use mobile sensor data, especially from accelerometers, to detect physical activity (type, duration, and intensity), sedentary behavior, and sleep in adults and children.
Collaborator(s): EveryFit, Inc., Stanford Medical School
Supported by: NIH/NCI and NIH/NHLBI
Although physical activity reduces the risk of chronic and mental health issues, low-income and racially marginalized communities are unable to exercise regularly because of systemic discrimination that constrains their ability to exercise. Our Storywell smartphone app demonstrated that community storytelling on fitness tracking data can support physical activity in marginalized communities. To further innovate in digital health storytelling, we are examining how just-in-time exercise storytelling from community members can further support physical activity.
Collaborators: Mattapan Food and Fitness Coalition
Supported by: Google
PHI Faculty: Matthew Goodwin
Stereotypical motor movements are one of the most common and least understood behaviors occurring in individuals with ASD. Stereotypical motor movements are complex and thought to serve a multiplicity of functions. While no one theory has obtained overwhelming support, there is evidence for biological, operant, and homeostatic interpretations.
Collaborator(s): MIT Media Lab, The Groden Center, Inc.
Supported by: Nancy Lurie Marks Family Foundation
PHI Faculty: Stephen Intille
This project is exploring how mobile technology can be used to support active commuting via bicycling, where individuals who would normally be commuting by car may instead commute via bicycle. They may do this because of a novel technological system that would create a car-free riding experience, dramatically enhancing comfort and safety.
PHI Faculty: Stephen Intille
Longitudinal sensor data collected passively from wearable activity monitors and mobile phones will transform behavioral science by allowing researchers to use “big data,” but at the person-level, to understand how behavior and related environmental exposures impact health outcomes and personalize health intervention and research. We propose to develop and test a system that permits typical mobile application game players to help scientists improve this type of data, by adding additional annotations that enrich the data, making it more useful for behavioral science and more amenable to automatic processing. This will help researchers to better understand how individual-level behaviors relate to health outcomes in current research studies that collect personal-level sensor data such as NHANES and the Women’s Health Study, and future big data ventures such as the new Precision Medicine Initiative.
Collaborators: Dinesh John (Northeastern University), Seth Cooper (Northeastern University)
Supported by: NIH
PHI Faculty: Timothy Bickmore
The purpose of this project is to develop a conversational agent system that counsels terminally ill patients in order to alleviate their suffering and improve their quality of life. Although many interventions have now been developed to address palliative care for specific chronic diseases, little has been done to address the overall quality of life for older adults with serious illness, spanning not only the functional aspects of symptom and medication management, but the affective aspects of suffering. In this project, we are developing a relational agent to counsel patients at home about medication adherence, stress management, advanced care planning, and spiritual support, and to provide referrals to palliative care services when needed.
Collaborators: Boston Medical Center
Supported by: NIH National Institute for Nursing Research
We are working with communities in a network of predominately African American churches in the Boston area, along with their Health Ministries and church leadership, to improve the overall health of church members. The intervention leverages a smartphone-based conversational agent that promotes physical activity, nutrition, healthy hydration, stress reduction through guided meditation, mental health care treatment, domestic violence awareness, and COVID and influenza vaccination.
Collaborators: Black Ministerial Alliance TenPoint of Boston, Dr. Michael Paasche-Orlow (Tufts Medical Center), Profs. Stephen Intille and Jessica Hoffman (Northeastern), Andrea Parker (Georgia Tech), Drs. Julien Dedier, Rebecca Perkins, and Natalie Joseph (Boston Medical Center).
Supported by: National Science Foundation and the NIH National Institute on Minority Health and Health Disparities
PHI Faculty: Cody Dunne, Stephen Intille
Type 1 diabetes (T1D), also called insulin dependent diabetes and juvenile diabetes, is an autoimmune disease which afflicts 1.25 million Americans. There are 40 thousand new diagnoses each year, and almost half of those are children and adolescents under age 20 years. The costs for our healthcare system are enormous, estimated at $14 billion annually. T1D is incurable, and people with T1D are estimated to lose over 10 years from their life expectancy. We are designing, building, and evaluating interactive visualization tools to help T1D patients and their caregivers make treatment decisions. In these visualizations we are showing data we collect using multiple devices and have data on the patient blood glucose levels, insulin administered, food eaten, exercise, and stress to name a few. Our tools are used by patients to understand the trends between scheduled events such as mealtimes, bedtimes, and overnight as well as irregular events like periods of exercise, stress, and illness. With this information, patients will be able to make more informed changes to their treatment protocols.
Collaborator: Boston Children’s Hospital
PHI Faculty: Timothy Bickmore
Most persons with spinal cord injury (SCI) require training and support for self-care management to help prevent the development of serious secondary conditions after hospital discharge. However, adherence to self-care management behaviors is poor once training with a therapist has ended. We have designed a virtual coach system, in which a relational agent engages individuals with SCI in simulated face-to-face conversations at home, to provide support and motivate adherence to self-care guidelines.
Collaborators: Boston University School of Public Health
Supported by: Nielsen Foundation
PHI Faculty: Stephen Intille
We are working on a variety of projects studying how to use mobile sensor data, especially from accelerometers, to detect physical activity (type, duration, and intensity), sedentary behavior, and sleep in adults and children.
Collaborator(s): EveryFit, Inc., Stanford Medical School
Supported by: NIH/NCI and NIH/NHLBI
Although physical activity reduces the risk of chronic and mental health issues, low-income and racially marginalized communities are unable to exercise regularly because of systemic discrimination that constrains their ability to exercise. Our Storywell smartphone app demonstrated that community storytelling on fitness tracking data can support physical activity in marginalized communities. To further innovate in digital health storytelling, we are examining how just-in-time exercise storytelling from community members can further support physical activity.
Collaborators: Mattapan Food and Fitness Coalition
Supported by: Google
PHI Faculty: Matthew Goodwin
Stereotypical motor movements are one of the most common and least understood behaviors occurring in individuals with ASD. Stereotypical motor movements are complex and thought to serve a multiplicity of functions. While no one theory has obtained overwhelming support, there is evidence for biological, operant, and homeostatic interpretations.
Collaborator(s): MIT Media Lab, The Groden Center, Inc.
Supported by: Nancy Lurie Marks Family Foundation
PHI Faculty: Stephen Intille
This project is exploring how mobile technology can be used to support active commuting via bicycling, where individuals who would normally be commuting by car may instead commute via bicycle. They may do this because of a novel technological system that would create a car-free riding experience, dramatically enhancing comfort and safety.
PHI Faculty: Stephen Intille
Longitudinal sensor data collected passively from wearable activity monitors and mobile phones will transform behavioral science by allowing researchers to use “big data,” but at the person-level, to understand how behavior and related environmental exposures impact health outcomes and personalize health intervention and research. We propose to develop and test a system that permits typical mobile application game players to help scientists improve this type of data, by adding additional annotations that enrich the data, making it more useful for behavioral science and more amenable to automatic processing. This will help researchers to better understand how individual-level behaviors relate to health outcomes in current research studies that collect personal-level sensor data such as NHANES and the Women’s Health Study, and future big data ventures such as the new Precision Medicine Initiative.
Collaborators: Dinesh John (Northeastern University), Seth Cooper (Northeastern University)
Supported by: NIH
PHI Faculty: Timothy Bickmore
The purpose of this project is to develop a conversational agent system that counsels terminally ill patients in order to alleviate their suffering and improve their quality of life. Although many interventions have now been developed to address palliative care for specific chronic diseases, little has been done to address the overall quality of life for older adults with serious illness, spanning not only the functional aspects of symptom and medication management, but the affective aspects of suffering. In this project, we are developing a relational agent to counsel patients at home about medication adherence, stress management, advanced care planning, and spiritual support, and to provide referrals to palliative care services when needed.
Collaborators: Boston Medical Center
Supported by: NIH National Institute for Nursing Research
We are working with communities in a network of predominately African American churches in the Boston area, along with their Health Ministries and church leadership, to improve the overall health of church members. The intervention leverages a smartphone-based conversational agent that promotes physical activity, nutrition, healthy hydration, stress reduction through guided meditation, mental health care treatment, domestic violence awareness, and COVID and influenza vaccination.
Collaborators: Black Ministerial Alliance TenPoint of Boston, Dr. Michael Paasche-Orlow (Tufts Medical Center), Profs. Stephen Intille and Jessica Hoffman (Northeastern), Andrea Parker (Georgia Tech), Drs. Julien Dedier, Rebecca Perkins, and Natalie Joseph (Boston Medical Center).
Supported by: National Science Foundation and the NIH National Institute on Minority Health and Health Disparities
PHI Faculty: Cody Dunne, Stephen Intille
Type 1 diabetes (T1D), also called insulin dependent diabetes and juvenile diabetes, is an autoimmune disease which afflicts 1.25 million Americans. There are 40 thousand new diagnoses each year, and almost half of those are children and adolescents under age 20 years. The costs for our healthcare system are enormous, estimated at $14 billion annually. T1D is incurable, and people with T1D are estimated to lose over 10 years from their life expectancy. We are designing, building, and evaluating interactive visualization tools to help T1D patients and their caregivers make treatment decisions. In these visualizations we are showing data we collect using multiple devices and have data on the patient blood glucose levels, insulin administered, food eaten, exercise, and stress to name a few. Our tools are used by patients to understand the trends between scheduled events such as mealtimes, bedtimes, and overnight as well as irregular events like periods of exercise, stress, and illness. With this information, patients will be able to make more informed changes to their treatment protocols.
Collaborator: Boston Children’s Hospital
PHI Faculty: Timothy Bickmore
Most persons with spinal cord injury (SCI) require training and support for self-care management to help prevent the development of serious secondary conditions after hospital discharge. However, adherence to self-care management behaviors is poor once training with a therapist has ended. We have designed a virtual coach system, in which a relational agent engages individuals with SCI in simulated face-to-face conversations at home, to provide support and motivate adherence to self-care guidelines.
Collaborators: Boston University School of Public Health
Supported by: Nielsen Foundation
PHI Faculty: Stephen Intille
We are working on a variety of projects studying how to use mobile sensor data, especially from accelerometers, to detect physical activity (type, duration, and intensity), sedentary behavior, and sleep in adults and children.
Collaborator(s): EveryFit, Inc., Stanford Medical School
Supported by: NIH/NCI and NIH/NHLBI
Although physical activity reduces the risk of chronic and mental health issues, low-income and racially marginalized communities are unable to exercise regularly because of systemic discrimination that constrains their ability to exercise. Our Storywell smartphone app demonstrated that community storytelling on fitness tracking data can support physical activity in marginalized communities. To further innovate in digital health storytelling, we are examining how just-in-time exercise storytelling from community members can further support physical activity.
Collaborators: Mattapan Food and Fitness Coalition
Supported by: Google
PHI Faculty: Matthew Goodwin
Stereotypical motor movements are one of the most common and least understood behaviors occurring in individuals with ASD. Stereotypical motor movements are complex and thought to serve a multiplicity of functions. While no one theory has obtained overwhelming support, there is evidence for biological, operant, and homeostatic interpretations.
Collaborator(s): MIT Media Lab, The Groden Center, Inc.
Supported by: Nancy Lurie Marks Family Foundation
PHI Faculty: Stephen Intille
This project is exploring how mobile technology can be used to support active commuting via bicycling, where individuals who would normally be commuting by car may instead commute via bicycle. They may do this because of a novel technological system that would create a car-free riding experience, dramatically enhancing comfort and safety.
PHI Faculty: Stephen Intille
Longitudinal sensor data collected passively from wearable activity monitors and mobile phones will transform behavioral science by allowing researchers to use “big data,” but at the person-level, to understand how behavior and related environmental exposures impact health outcomes and personalize health intervention and research. We propose to develop and test a system that permits typical mobile application game players to help scientists improve this type of data, by adding additional annotations that enrich the data, making it more useful for behavioral science and more amenable to automatic processing. This will help researchers to better understand how individual-level behaviors relate to health outcomes in current research studies that collect personal-level sensor data such as NHANES and the Women’s Health Study, and future big data ventures such as the new Precision Medicine Initiative.
Collaborators: Dinesh John (Northeastern University), Seth Cooper (Northeastern University)
Supported by: NIH
PHI Faculty: Timothy Bickmore
The purpose of this project is to develop a conversational agent system that counsels terminally ill patients in order to alleviate their suffering and improve their quality of life. Although many interventions have now been developed to address palliative care for specific chronic diseases, little has been done to address the overall quality of life for older adults with serious illness, spanning not only the functional aspects of symptom and medication management, but the affective aspects of suffering. In this project, we are developing a relational agent to counsel patients at home about medication adherence, stress management, advanced care planning, and spiritual support, and to provide referrals to palliative care services when needed.
Collaborators: Boston Medical Center
Supported by: NIH National Institute for Nursing Research
We are working with communities in a network of predominately African American churches in the Boston area, along with their Health Ministries and church leadership, to improve the overall health of church members. The intervention leverages a smartphone-based conversational agent that promotes physical activity, nutrition, healthy hydration, stress reduction through guided meditation, mental health care treatment, domestic violence awareness, and COVID and influenza vaccination.
Collaborators: Black Ministerial Alliance TenPoint of Boston, Dr. Michael Paasche-Orlow (Tufts Medical Center), Profs. Stephen Intille and Jessica Hoffman (Northeastern), Andrea Parker (Georgia Tech), Drs. Julien Dedier, Rebecca Perkins, and Natalie Joseph (Boston Medical Center).
Supported by: National Science Foundation and the NIH National Institute on Minority Health and Health Disparities
PHI Faculty: Cody Dunne, Stephen Intille
Type 1 diabetes (T1D), also called insulin dependent diabetes and juvenile diabetes, is an autoimmune disease which afflicts 1.25 million Americans. There are 40 thousand new diagnoses each year, and almost half of those are children and adolescents under age 20 years. The costs for our healthcare system are enormous, estimated at $14 billion annually. T1D is incurable, and people with T1D are estimated to lose over 10 years from their life expectancy. We are designing, building, and evaluating interactive visualization tools to help T1D patients and their caregivers make treatment decisions. In these visualizations we are showing data we collect using multiple devices and have data on the patient blood glucose levels, insulin administered, food eaten, exercise, and stress to name a few. Our tools are used by patients to understand the trends between scheduled events such as mealtimes, bedtimes, and overnight as well as irregular events like periods of exercise, stress, and illness. With this information, patients will be able to make more informed changes to their treatment protocols.
Collaborator: Boston Children’s Hospital
PHI Faculty: Timothy Bickmore
Most persons with spinal cord injury (SCI) require training and support for self-care management to help prevent the development of serious secondary conditions after hospital discharge. However, adherence to self-care management behaviors is poor once training with a therapist has ended. We have designed a virtual coach system, in which a relational agent engages individuals with SCI in simulated face-to-face conversations at home, to provide support and motivate adherence to self-care guidelines.
Collaborators: Boston University School of Public Health
Supported by: Nielsen Foundation
PHI Faculty: Stephen Intille
We are working on a variety of projects studying how to use mobile sensor data, especially from accelerometers, to detect physical activity (type, duration, and intensity), sedentary behavior, and sleep in adults and children.
Collaborator(s): EveryFit, Inc., Stanford Medical School
Supported by: NIH/NCI and NIH/NHLBI
Although physical activity reduces the risk of chronic and mental health issues, low-income and racially marginalized communities are unable to exercise regularly because of systemic discrimination that constrains their ability to exercise. Our Storywell smartphone app demonstrated that community storytelling on fitness tracking data can support physical activity in marginalized communities. To further innovate in digital health storytelling, we are examining how just-in-time exercise storytelling from community members can further support physical activity.
Collaborators: Mattapan Food and Fitness Coalition
Supported by: Google
PHI Faculty: Matthew Goodwin
Stereotypical motor movements are one of the most common and least understood behaviors occurring in individuals with ASD. Stereotypical motor movements are complex and thought to serve a multiplicity of functions. While no one theory has obtained overwhelming support, there is evidence for biological, operant, and homeostatic interpretations.
Collaborator(s): MIT Media Lab, The Groden Center, Inc.
Supported by: Nancy Lurie Marks Family Foundation
PHI Faculty: Stephen Intille
This project is exploring how mobile technology can be used to support active commuting via bicycling, where individuals who would normally be commuting by car may instead commute via bicycle. They may do this because of a novel technological system that would create a car-free riding experience, dramatically enhancing comfort and safety.
PHI Faculty: Stephen Intille
Longitudinal sensor data collected passively from wearable activity monitors and mobile phones will transform behavioral science by allowing researchers to use “big data,” but at the person-level, to understand how behavior and related environmental exposures impact health outcomes and personalize health intervention and research. We propose to develop and test a system that permits typical mobile application game players to help scientists improve this type of data, by adding additional annotations that enrich the data, making it more useful for behavioral science and more amenable to automatic processing. This will help researchers to better understand how individual-level behaviors relate to health outcomes in current research studies that collect personal-level sensor data such as NHANES and the Women’s Health Study, and future big data ventures such as the new Precision Medicine Initiative.
Collaborators: Dinesh John (Northeastern University), Seth Cooper (Northeastern University)
Supported by: NIH
PHI Faculty: Timothy Bickmore
The purpose of this project is to develop a conversational agent system that counsels terminally ill patients in order to alleviate their suffering and improve their quality of life. Although many interventions have now been developed to address palliative care for specific chronic diseases, little has been done to address the overall quality of life for older adults with serious illness, spanning not only the functional aspects of symptom and medication management, but the affective aspects of suffering. In this project, we are developing a relational agent to counsel patients at home about medication adherence, stress management, advanced care planning, and spiritual support, and to provide referrals to palliative care services when needed.
Collaborators: Boston Medical Center
Supported by: NIH National Institute for Nursing Research
We are working with communities in a network of predominately African American churches in the Boston area, along with their Health Ministries and church leadership, to improve the overall health of church members. The intervention leverages a smartphone-based conversational agent that promotes physical activity, nutrition, healthy hydration, stress reduction through guided meditation, mental health care treatment, domestic violence awareness, and COVID and influenza vaccination.
Collaborators: Black Ministerial Alliance TenPoint of Boston, Dr. Michael Paasche-Orlow (Tufts Medical Center), Profs. Stephen Intille and Jessica Hoffman (Northeastern), Andrea Parker (Georgia Tech), Drs. Julien Dedier, Rebecca Perkins, and Natalie Joseph (Boston Medical Center).
Supported by: National Science Foundation and the NIH National Institute on Minority Health and Health Disparities
PHI Faculty: Cody Dunne, Stephen Intille
Type 1 diabetes (T1D), also called insulin dependent diabetes and juvenile diabetes, is an autoimmune disease which afflicts 1.25 million Americans. There are 40 thousand new diagnoses each year, and almost half of those are children and adolescents under age 20 years. The costs for our healthcare system are enormous, estimated at $14 billion annually. T1D is incurable, and people with T1D are estimated to lose over 10 years from their life expectancy. We are designing, building, and evaluating interactive visualization tools to help T1D patients and their caregivers make treatment decisions. In these visualizations we are showing data we collect using multiple devices and have data on the patient blood glucose levels, insulin administered, food eaten, exercise, and stress to name a few. Our tools are used by patients to understand the trends between scheduled events such as mealtimes, bedtimes, and overnight as well as irregular events like periods of exercise, stress, and illness. With this information, patients will be able to make more informed changes to their treatment protocols.
Collaborator: Boston Children’s Hospital
PHI Faculty: Timothy Bickmore
Most persons with spinal cord injury (SCI) require training and support for self-care management to help prevent the development of serious secondary conditions after hospital discharge. However, adherence to self-care management behaviors is poor once training with a therapist has ended. We have designed a virtual coach system, in which a relational agent engages individuals with SCI in simulated face-to-face conversations at home, to provide support and motivate adherence to self-care guidelines.
Collaborators: Boston University School of Public Health
Supported by: Nielsen Foundation
PHI Faculty: Stephen Intille
We are working on a variety of projects studying how to use mobile sensor data, especially from accelerometers, to detect physical activity (type, duration, and intensity), sedentary behavior, and sleep in adults and children.
Collaborator(s): EveryFit, Inc., Stanford Medical School
Supported by: NIH/NCI and NIH/NHLBI
Although physical activity reduces the risk of chronic and mental health issues, low-income and racially marginalized communities are unable to exercise regularly because of systemic discrimination that constrains their ability to exercise. Our Storywell smartphone app demonstrated that community storytelling on fitness tracking data can support physical activity in marginalized communities. To further innovate in digital health storytelling, we are examining how just-in-time exercise storytelling from community members can further support physical activity.
Collaborators: Mattapan Food and Fitness Coalition
Supported by: Google
PHI Faculty: Matthew Goodwin
Stereotypical motor movements are one of the most common and least understood behaviors occurring in individuals with ASD. Stereotypical motor movements are complex and thought to serve a multiplicity of functions. While no one theory has obtained overwhelming support, there is evidence for biological, operant, and homeostatic interpretations.
Collaborator(s): MIT Media Lab, The Groden Center, Inc.
Supported by: Nancy Lurie Marks Family Foundation
PHI Faculty: Stephen Intille
This project is exploring how mobile technology can be used to support active commuting via bicycling, where individuals who would normally be commuting by car may instead commute via bicycle. They may do this because of a novel technological system that would create a car-free riding experience, dramatically enhancing comfort and safety.
PHI Faculty: Stephen Intille
Longitudinal sensor data collected passively from wearable activity monitors and mobile phones will transform behavioral science by allowing researchers to use “big data,” but at the person-level, to understand how behavior and related environmental exposures impact health outcomes and personalize health intervention and research. We propose to develop and test a system that permits typical mobile application game players to help scientists improve this type of data, by adding additional annotations that enrich the data, making it more useful for behavioral science and more amenable to automatic processing. This will help researchers to better understand how individual-level behaviors relate to health outcomes in current research studies that collect personal-level sensor data such as NHANES and the Women’s Health Study, and future big data ventures such as the new Precision Medicine Initiative.
Collaborators: Dinesh John (Northeastern University), Seth Cooper (Northeastern University)
Supported by: NIH
PHI Faculty: Timothy Bickmore
The purpose of this project is to develop a conversational agent system that counsels terminally ill patients in order to alleviate their suffering and improve their quality of life. Although many interventions have now been developed to address palliative care for specific chronic diseases, little has been done to address the overall quality of life for older adults with serious illness, spanning not only the functional aspects of symptom and medication management, but the affective aspects of suffering. In this project, we are developing a relational agent to counsel patients at home about medication adherence, stress management, advanced care planning, and spiritual support, and to provide referrals to palliative care services when needed.
Collaborators: Boston Medical Center
Supported by: NIH National Institute for Nursing Research
We are working with communities in a network of predominately African American churches in the Boston area, along with their Health Ministries and church leadership, to improve the overall health of church members. The intervention leverages a smartphone-based conversational agent that promotes physical activity, nutrition, healthy hydration, stress reduction through guided meditation, mental health care treatment, domestic violence awareness, and COVID and influenza vaccination.
Collaborators: Black Ministerial Alliance TenPoint of Boston, Dr. Michael Paasche-Orlow (Tufts Medical Center), Profs. Stephen Intille and Jessica Hoffman (Northeastern), Andrea Parker (Georgia Tech), Drs. Julien Dedier, Rebecca Perkins, and Natalie Joseph (Boston Medical Center).
Supported by: National Science Foundation and the NIH National Institute on Minority Health and Health Disparities
PHI Faculty: Cody Dunne, Stephen Intille
Type 1 diabetes (T1D), also called insulin dependent diabetes and juvenile diabetes, is an autoimmune disease which afflicts 1.25 million Americans. There are 40 thousand new diagnoses each year, and almost half of those are children and adolescents under age 20 years. The costs for our healthcare system are enormous, estimated at $14 billion annually. T1D is incurable, and people with T1D are estimated to lose over 10 years from their life expectancy. We are designing, building, and evaluating interactive visualization tools to help T1D patients and their caregivers make treatment decisions. In these visualizations we are showing data we collect using multiple devices and have data on the patient blood glucose levels, insulin administered, food eaten, exercise, and stress to name a few. Our tools are used by patients to understand the trends between scheduled events such as mealtimes, bedtimes, and overnight as well as irregular events like periods of exercise, stress, and illness. With this information, patients will be able to make more informed changes to their treatment protocols.
Collaborator: Boston Children’s Hospital
PHI Faculty: Timothy Bickmore
Most persons with spinal cord injury (SCI) require training and support for self-care management to help prevent the development of serious secondary conditions after hospital discharge. However, adherence to self-care management behaviors is poor once training with a therapist has ended. We have designed a virtual coach system, in which a relational agent engages individuals with SCI in simulated face-to-face conversations at home, to provide support and motivate adherence to self-care guidelines.
Collaborators: Boston University School of Public Health
Supported by: Nielsen Foundation
PHI Faculty: Stephen Intille
We are working on a variety of projects studying how to use mobile sensor data, especially from accelerometers, to detect physical activity (type, duration, and intensity), sedentary behavior, and sleep in adults and children.
Collaborator(s): EveryFit, Inc., Stanford Medical School
Supported by: NIH/NCI and NIH/NHLBI