Alex Page | University of Rochester (original) (raw)

Papers by Alex Page

Cardiovascular Digital Health Journal

Cardiovascular Digital Health Journal

Digital Biomarkers, 2022

Background: Smartphones can generate objective measures of Parkinson’s disease (PD) and supplemen... more Background: Smartphones can generate objective measures of Parkinson’s disease (PD) and supplement traditional in-person rating scales. However, smartphone use in clinical trials has been limited. Objective: This study aimed to determine the feasibility of introducing a smartphone research application into a PD clinical trial and to evaluate the resulting measures. Methods: A smartphone application was introduced part-way into a phase 3 randomized clinical trial of inosine. The application included finger tapping, gait, and cognition tests, and participants were asked to complete an assessment battery at home and in clinic alongside the Movement Disorder Society-Unified Parkinson’s Disease Rating Scale (MDS-UPDRS). Results: Of 236 eligible participants in the parent study, 88 (37%) consented to participate, and 59 (27 randomized to inosine and 32 to placebo) completed a baseline smartphone assessment. These 59 participants collectively completed 1,292 batteries of assessments. The p...

Digital Biomarkers, 2022

Background: Smartphones can generate objective measures of Parkinson’s disease (PD) and supplemen... more Background: Smartphones can generate objective measures of Parkinson’s disease (PD) and supplement traditional in-person rating scales. However, smartphone use in clinical trials has been limited. Objective: This study aimed to determine the feasibility of introducing a smartphone research application into a PD clinical trial and to evaluate the resulting measures. Methods: A smartphone application was introduced part-way into a phase 3 randomized clinical trial of inosine. The application included finger tapping, gait, and cognition tests, and participants were asked to complete an assessment battery at home and in clinic alongside the Movement Disorder Society-Unified Parkinson’s Disease Rating Scale (MDS-UPDRS). Results: Of 236 eligible participants in the parent study, 88 (37%) consented to participate, and 59 (27 randomized to inosine and 32 to placebo) completed a baseline smartphone assessment. These 59 participants collectively completed 1,292 batteries of assessments. The p...

International Journal of Heart Rhythm, 2021

Rhythm Society describes the current status of mobile health technologies in arrhythmia managemen... more Rhythm Society describes the current status of mobile health technologies in arrhythmia management. The range of digital medical tools and heart rhythm disorders that they may be applied to and clinical decisions that may be enabled are discussed. The facilitation of comorbidity and lifestyle management (increasingly recognized to play a role in heart rhythm disorders) and patient self-management are novel aspects of mobile health. The promises of predictive analytics but also operational challenges in embedding mobile health into routine clinical care are explored.

International Journal of Heart Rhythm, 2021

Rhythm Society describes the current status of mobile health technologies in arrhythmia managemen... more Rhythm Society describes the current status of mobile health technologies in arrhythmia management. The range of digital medical tools and heart rhythm disorders that they may be applied to and clinical decisions that may be enabled are discussed. The facilitation of comorbidity and lifestyle management (increasingly recognized to play a role in heart rhythm disorders) and patient self-management are novel aspects of mobile health. The promises of predictive analytics but also operational challenges in embedding mobile health into routine clinical care are explored.

Services Transactions on Services Computing, 2016

The Digital Health (D-Health) era is expected to be the "next big thing" since the invention of t... more The Digital Health (D-Health) era is expected to be the "next big thing" since the invention of the internet, characterized by inexpensive and widespread medical data acquisition devices, widespread availability of identityremoved health data, and analytics algorithms that provide remote health monitoring feedback to doctors in realtime. Recent years have brought incremental developments in three key technological areas towards the realization of the D-Health era: data acquisition, secure data transmission/storage, and data analytics. i) For data acquisition, the emerging Internet-of-Things (IoT) devices are becoming a viable technology to enable the acquisition of remote health monitoring data. ii) For data storage, emerging system-level and cryptographic mechanisms provide secure and privacy-preserving transmission, storage, and sharing of the acquired data. iii) For data analytics, emerging decision support algorithms provide a mechanism for healthcare professionals to base their clinical diagnoses partially on machine-suggested statistical inferences that rely on a wide corpus of accumulated data. The D-Health era will create new business opportunities in all of these areas. In this paper, we propose a generalized structure for a D-Health system that is capable of remote health monitoring and decision support. We formulate our proposed structure around potential business opportunities and conduct technical feasibility studies.

The advent of portable medical sensors such as electrocardiograms has enabled widespread remote m... more The advent of portable medical sensors such as electrocardiograms has enabled widespread remote monitoring. The data collected from such devices presents new research opportunities and challenges to improve diagnosis and treatment for every individual patient. Condensing the sensor data into a form that is useful for doctors and researchers is the focus of this work. In particular, I investigate techniques to streamline the handling and processing of large data sets, the utility of long-term monitoring data (such as Holter ECG recordings) in decision support, and the application of machine learning in risk stratification. To support this process, I explain a system for automatically delineating key markers in ECG recordings, and displaying them in a novel way for identification of anomalies or patterns. I then show how this method can be used in drug studies, as well as to unmask potential problems in patients with certain genetic disorders. Finally, machine learning and statistical...

The United States Coast Guard (USCG) is a military, multi-mission, maritime service within the De... more The United States Coast Guard (USCG) is a military, multi-mission, maritime service within the Department of Homeland Security (DHS). Its core roles are to protect the public, the environment, and U.S. economic and security interests in any maritime region in which those interests may be at risk. The USCG has become increasingly dependent on Global Navigation Satellite Systems (GNSS), especially the US Global Positioning Service (GPS), in order to conduct its missions more efficiently and effectively. The USCG has operated Nationwide Differential GPS (NDGPS) through a network of 85+ remote broadcast sites since 1999 to enhance user receiver position accuracy and integrity. Significant investments were made in recent years to enhance that system by replacing aging reference stations, integrity monitors, and transmitters with state of the art equipment. Results of preliminary and informal studies indicate increases in performance, specifically accuracy and availability, suggesting the need for a more formal review. The current performance standard for NDGPS dates back to the April 1993 Broadcast Standard, which requires a 10-meter (m) 2drms system over the coverage areas. This also is the basis for the US agreeing to Harbor and Harbor Approach requirements found in IALA R-121 and IMO Resolution A.953(23). The specification was derived based on spatial decorrelation, or the degradation of the accuracy of the DGPS correction over increasing baselines between the reference station and rover, as well as in the Horizontal Dilution of Precision (HDOP). The 10m standard also accounted for Selective Availability (S/A), an intentional degradation of the GPS signal applied in order to provide the intended military user with more precise accuracies than was available to civilian users. S/A was turned off by direction of a Presidential Order in 2000. The present GPS L1 Standard Positioning Service (SPS) performance specification is error ≤ 7.8m (2drms) for single frequency Course Acquisition (C/A) code, global average User Range Error (URE) during normal operations. The combination of this current GPS performance statement, preliminary studies of positioning performance following recent NDGPS recapitalization, and the disabling of S/A, together necessitate a detailed re-evaluation of the performance of the current NDGPS system and refinement of the spatial decorrelation model. The primary objectives of this study are to determine the accuracy of the NDGPS for the typical user and the development of an updated spatial decorrelation model for performance as a function of distance from the NDPGS reference site (the current model from the 1993 Broadcast Standard, is 2 meters plus 1 meter per 150 km from the beacon site). Simulation, software processing of existing GPS data sets (available from the Continuously Operating Reference Station or CORS, network) at a collection of spatially dispersed sites with the same NDGPS corrections, and actual field measurements at selected sites provides data for these objectives. This current paper provides results from all testing to date

One of the promising opportunities of digital health is its potential to lead to more holistic un... more One of the promising opportunities of digital health is its potential to lead to more holistic understandings of diseases by interacting with the daily life of patients and through the collection of large amounts of real world data. Validating and benchmarking indicators of disease severity in the home setting is difficult, however, given the large number of confounders present in the real world and the challenges in collecting ground truth data in the home. Here we leverage two datasets with continuous wrist-worn accelerometer data coupled with frequent symptom reports in the home setting, to develop digital biomarkers of symptom severity. Using these data, we performed a public benchmarking challenge in which participants were asked to build measures of severity across 3 symptoms (on/off medication, dyskinesia, and tremor). 42 teams participated and performance was improved over baseline models for each subchallenge. Additional ensemble modeling across submissions further improved...

Annals of Noninvasive Electrocardiology, 2021

Atrial fibrillation (AF) is the most common arrhythmia, and despite progress with catheter ablati... more Atrial fibrillation (AF) is the most common arrhythmia, and despite progress with catheter ablation and pulmonary vein isolation, there is a need for pharmacological treatment alternatives. Few new pharmacological options have been added during the last decade and there is a need for improved risk markers to avoid pro-arrhythmias (Lafuente-Lafuente et al., 2012).

Circulation: Arrhythmia and Electrophysiology, 2021

This collaborative statement from the International Society for Holter and Noninvasive Electrocar... more This collaborative statement from the International Society for Holter and Noninvasive Electrocardiology/Heart Rhythm Society/European Heart Rhythm Association/Asia-Pacific Heart Rhythm Society describes the current status of mobile health technologies in arrhythmia management. The range of digital medical tools and heart rhythm disorders that they may be applied to and clinical decisions that may be enabled are discussed. The facilitation of comorbidity and lifestyle management (increasingly recognized to play a role in heart rhythm disorders) and patient self-management are novel aspects of mobile health. The promises of predictive analytics but also operational challenges in embedding mobile health into routine clinical care are explored.

Annals of Noninvasive Electrocardiology, 2021

This collaborative statement from the International Society for Holter and Noninvasive Electrocar... more This collaborative statement from the International Society for Holter and Noninvasive Electrocardiology/Heart Rhythm Society/European Heart Rhythm Association/Asia Pacific Heart Rhythm Society describes the current status of mobile health ("mHealth") technologies in arrhythmia management. The range of digital medical tools and heart rhythm disorders that they may be applied to and clinical decisions that may be enabled are discussed. The facilitation of comorbidity and lifestyle management (increasingly recognized to play a role in heart rhythm disorders) and patient self-management are novel aspects of mHealth. The promises of predictive analytics but also operational challenges in embedding mHealth into routine clinical care are explored.

Journal of Electrocardiology, 2017

The increasing dissemination of wearable ECG recorders (e.g. Holter, patches, and strap sensors) ... more The increasing dissemination of wearable ECG recorders (e.g. Holter, patches, and strap sensors) enables the acquisition of large amounts of data during long periods of time. However, the clinical value of these long-term continuous recordings is hindered by the lack of automatic tools to extract clinically relevant information (other than non-sinus and lifethreatening rhythms) from such long-term data, particularly when targeting population-based research. In this work, we propose and test a new tool for analyzing beat-to-beat interval measurements and extracting features from Holter ECGs. Specifically, we assess the adaptation of the QT interval following sudden changes in heart rate in the primary long QT types (1 & 2). We find that in long QT syndrome type 2, certain QT adaptation patterns can indicate a higher risk for cardiac events.

Journal of Electrocardiology, 2017

Interest in the effects of drugs on the heart rate-corrected JTpeak (JTpc) interval from the body... more Interest in the effects of drugs on the heart rate-corrected JTpeak (JTpc) interval from the body-surface ECG has spawned an increasing number of scientific investigations in the field of regulatory sciences, and more specifically in the context of the Comprehensive in vitro Proarrhythmia Assay (CiPA) initiative. We conducted a novel initiative to evaluate the role of automatic JTpc measurement technologies by comparing their ability to distinguish multi-from single-channel blocking drugs. A set of 5,232 ECGs was shared by the FDA (through the Telemetric and Holter ECG Warehouse) with 3 ECG device companies (AMPS, Mortara, and Philips). We evaluated the differences in drug-concentration effects on these measurements between the commercial and the FDA technologies. We provide a description of the druginduced placebo-corrected changes from baseline for dofetilide, quinidine, ranolazine, and verapamil, and discuss the various differences across all technologies. The results revealed only small differences between measurement technologies confirming that the JTpc interval distinguishes between multi-and single-channel (hERG) blocking drugs when evaluating the effects of dofetilide, quinidine, ranolazine, and verapamil. In the case of quinidine and dofetilide, we noticed a poor consistency across technologies because of the lack of standard definitions for the location of the peak of the Twave (T-apex) when the T-wave morphology is abnormal.

Computer, 2016

Portable medical devices generate volumes of data that could be useful in identifying health risk... more Portable medical devices generate volumes of data that could be useful in identifying health risks. The proposed method filters patients' electrocardiograms (ECGs) and applies machine-learning classifiers to identify cardiac health risks and estimate severity. The authors present the results of applying their method in a case study.

2016 IEEE Symposium on Computers and Communication (ISCC), 2016

The past few decades have witnessed incredible advances in human health care, owing to the invent... more The past few decades have witnessed incredible advances in human health care, owing to the invention of devices such as MRI scanners, which allow physicians to monitor personal health in more detail than was ever previously possible. Such advances have drastically improved diagnostic quality and patient health care. Central to this incredible progress was the uncanny ability of technologists and academics to invent ever more useful tools to help physicians, be it the X-ray machine, CT, or MRI scanner. Whereas the aforementioned past-decades' tools aimed at acquiring personal data, the advent of the Internetof-Things, vast computational power available in the cloud, and new data analytics algorithms will completely change the way we acquire and process medical data to improve health care going forward. In this paper, we conduct a quantitative feasibility study of a Digital Health (D-Health) system that is aimed at acquiring and processing health data using the emerging Internet-of-Everything paradigm. We specifically investigate the technological feasibility of communication, software, and data privacy aspects.

2015 IEEE Global Communications Conference (GLOBECOM), 2014

As global healthcare systems transition into the digital era, remote patient health monitoring wi... more As global healthcare systems transition into the digital era, remote patient health monitoring will be widespread through the use of inexpensive monitoring devices, such as ECG patches, glucose monitors, etc. Once a sensor-concentratorcloudlet-cloud infrastructure is in place, it is not unrealistic to imagine a scenario where a physician monitors 20-30 patients remotely. Such an infrastructure will revolutionize clinical diagnostics and preventative medicine by allowing the doctors to access long-term and real-time information, which cannot be obtained from short-term in-hospital ECG recordings. While the large amount of sensor data available to a physician is incredibly valuable clinically, it is overwhelming in raw form. In this paper, the data handling aspect of such a long term health monitoring system is studied. Novel ways to record, aggregate, and visualize this flood of sensory data in an intuitive manner are introduced which allow a doctor to review days worth of data in a matter of seconds. This system is one of the first attempts to provide a tool that allows the visualization of longterm monitoring data acquired from multiple sensors.

IEEE Access, 2015

The collection of long term health data is accelerating with the advent of portable/wearable medi... more The collection of long term health data is accelerating with the advent of portable/wearable medical devices including electrocardiograms (ECGs). This large corpus of data presents great opportunities to improve the quality of cardiac care. However, analyzing the data from these sensors is a challenge; the relevant information from ∼120,000 heart beats per patient per day must be condensed into a human-readable form. Our goal is to facilitate the analysis of these unwieldy data sets. Methods: We have developed an open source tool for creating easy-to-interpret plots of cardiac information over long periods. We call these plots "ECG Clocks." The utility of our ECG Clock library is demonstrated through multiple examples drawn from a database of 24-hour Holter recordings. In these case studies, we focus on visualization of heart rate and QT dynamics. Results: The ECG Clock concept is shown to be relevant for both physicians and researchers, for identifying healthy and abnormal values and patterns in ECG recordings. Conclusion: In this paper, we describe how to use the ECG Clock library to analyze 24-hour ECG recordings, and how to extend the source code for your own purposes. The tool is applicable to a wide range of cardiac monitoring tasks, such as heart rate variability or ST elevation. Significance: This library, which we have made freely available, can help provide new insights into circadian patterns of cardiac function in individuals and groups.

Enabling Real-Time Mobile Cloud Computing through Emerging Technologies

In today's technology, even leading medical institutions diagnose their cardiac patients thro... more In today's technology, even leading medical institutions diagnose their cardiac patients through ECG recordings obtained at healthcare organizations (HCO), which are costly to obtain and may miss significant clinically-relevant information. Existing long-term patient monitoring systems (e.g., Holter monitors) provide limited information about the evolution of deadly cardiac conditions and lack interactivity in case there is a sudden degradation in the patient's health condition. A standardized and scalable system does not currently exist to monitor an expanding set of patient vitals that a doctor can prescribe to monitor. The design of such a system will translate to significant healthcare savings as well as drastic improvements in diagnostic accuracy. In this chapter, we will propose a concept system for real-time remote cardiac health monitoring, based on available and emerging technologies today. We will analyze the details of such a system from acquisition to visualizati...

Cardiovascular Digital Health Journal

Cardiovascular Digital Health Journal

Digital Biomarkers, 2022

Background: Smartphones can generate objective measures of Parkinson’s disease (PD) and supplemen... more Background: Smartphones can generate objective measures of Parkinson’s disease (PD) and supplement traditional in-person rating scales. However, smartphone use in clinical trials has been limited. Objective: This study aimed to determine the feasibility of introducing a smartphone research application into a PD clinical trial and to evaluate the resulting measures. Methods: A smartphone application was introduced part-way into a phase 3 randomized clinical trial of inosine. The application included finger tapping, gait, and cognition tests, and participants were asked to complete an assessment battery at home and in clinic alongside the Movement Disorder Society-Unified Parkinson’s Disease Rating Scale (MDS-UPDRS). Results: Of 236 eligible participants in the parent study, 88 (37%) consented to participate, and 59 (27 randomized to inosine and 32 to placebo) completed a baseline smartphone assessment. These 59 participants collectively completed 1,292 batteries of assessments. The p...

Digital Biomarkers, 2022

Background: Smartphones can generate objective measures of Parkinson’s disease (PD) and supplemen... more Background: Smartphones can generate objective measures of Parkinson’s disease (PD) and supplement traditional in-person rating scales. However, smartphone use in clinical trials has been limited. Objective: This study aimed to determine the feasibility of introducing a smartphone research application into a PD clinical trial and to evaluate the resulting measures. Methods: A smartphone application was introduced part-way into a phase 3 randomized clinical trial of inosine. The application included finger tapping, gait, and cognition tests, and participants were asked to complete an assessment battery at home and in clinic alongside the Movement Disorder Society-Unified Parkinson’s Disease Rating Scale (MDS-UPDRS). Results: Of 236 eligible participants in the parent study, 88 (37%) consented to participate, and 59 (27 randomized to inosine and 32 to placebo) completed a baseline smartphone assessment. These 59 participants collectively completed 1,292 batteries of assessments. The p...

International Journal of Heart Rhythm, 2021

Rhythm Society describes the current status of mobile health technologies in arrhythmia managemen... more Rhythm Society describes the current status of mobile health technologies in arrhythmia management. The range of digital medical tools and heart rhythm disorders that they may be applied to and clinical decisions that may be enabled are discussed. The facilitation of comorbidity and lifestyle management (increasingly recognized to play a role in heart rhythm disorders) and patient self-management are novel aspects of mobile health. The promises of predictive analytics but also operational challenges in embedding mobile health into routine clinical care are explored.

International Journal of Heart Rhythm, 2021

Rhythm Society describes the current status of mobile health technologies in arrhythmia managemen... more Rhythm Society describes the current status of mobile health technologies in arrhythmia management. The range of digital medical tools and heart rhythm disorders that they may be applied to and clinical decisions that may be enabled are discussed. The facilitation of comorbidity and lifestyle management (increasingly recognized to play a role in heart rhythm disorders) and patient self-management are novel aspects of mobile health. The promises of predictive analytics but also operational challenges in embedding mobile health into routine clinical care are explored.

Services Transactions on Services Computing, 2016

The Digital Health (D-Health) era is expected to be the "next big thing" since the invention of t... more The Digital Health (D-Health) era is expected to be the "next big thing" since the invention of the internet, characterized by inexpensive and widespread medical data acquisition devices, widespread availability of identityremoved health data, and analytics algorithms that provide remote health monitoring feedback to doctors in realtime. Recent years have brought incremental developments in three key technological areas towards the realization of the D-Health era: data acquisition, secure data transmission/storage, and data analytics. i) For data acquisition, the emerging Internet-of-Things (IoT) devices are becoming a viable technology to enable the acquisition of remote health monitoring data. ii) For data storage, emerging system-level and cryptographic mechanisms provide secure and privacy-preserving transmission, storage, and sharing of the acquired data. iii) For data analytics, emerging decision support algorithms provide a mechanism for healthcare professionals to base their clinical diagnoses partially on machine-suggested statistical inferences that rely on a wide corpus of accumulated data. The D-Health era will create new business opportunities in all of these areas. In this paper, we propose a generalized structure for a D-Health system that is capable of remote health monitoring and decision support. We formulate our proposed structure around potential business opportunities and conduct technical feasibility studies.

The advent of portable medical sensors such as electrocardiograms has enabled widespread remote m... more The advent of portable medical sensors such as electrocardiograms has enabled widespread remote monitoring. The data collected from such devices presents new research opportunities and challenges to improve diagnosis and treatment for every individual patient. Condensing the sensor data into a form that is useful for doctors and researchers is the focus of this work. In particular, I investigate techniques to streamline the handling and processing of large data sets, the utility of long-term monitoring data (such as Holter ECG recordings) in decision support, and the application of machine learning in risk stratification. To support this process, I explain a system for automatically delineating key markers in ECG recordings, and displaying them in a novel way for identification of anomalies or patterns. I then show how this method can be used in drug studies, as well as to unmask potential problems in patients with certain genetic disorders. Finally, machine learning and statistical...

The United States Coast Guard (USCG) is a military, multi-mission, maritime service within the De... more The United States Coast Guard (USCG) is a military, multi-mission, maritime service within the Department of Homeland Security (DHS). Its core roles are to protect the public, the environment, and U.S. economic and security interests in any maritime region in which those interests may be at risk. The USCG has become increasingly dependent on Global Navigation Satellite Systems (GNSS), especially the US Global Positioning Service (GPS), in order to conduct its missions more efficiently and effectively. The USCG has operated Nationwide Differential GPS (NDGPS) through a network of 85+ remote broadcast sites since 1999 to enhance user receiver position accuracy and integrity. Significant investments were made in recent years to enhance that system by replacing aging reference stations, integrity monitors, and transmitters with state of the art equipment. Results of preliminary and informal studies indicate increases in performance, specifically accuracy and availability, suggesting the need for a more formal review. The current performance standard for NDGPS dates back to the April 1993 Broadcast Standard, which requires a 10-meter (m) 2drms system over the coverage areas. This also is the basis for the US agreeing to Harbor and Harbor Approach requirements found in IALA R-121 and IMO Resolution A.953(23). The specification was derived based on spatial decorrelation, or the degradation of the accuracy of the DGPS correction over increasing baselines between the reference station and rover, as well as in the Horizontal Dilution of Precision (HDOP). The 10m standard also accounted for Selective Availability (S/A), an intentional degradation of the GPS signal applied in order to provide the intended military user with more precise accuracies than was available to civilian users. S/A was turned off by direction of a Presidential Order in 2000. The present GPS L1 Standard Positioning Service (SPS) performance specification is error ≤ 7.8m (2drms) for single frequency Course Acquisition (C/A) code, global average User Range Error (URE) during normal operations. The combination of this current GPS performance statement, preliminary studies of positioning performance following recent NDGPS recapitalization, and the disabling of S/A, together necessitate a detailed re-evaluation of the performance of the current NDGPS system and refinement of the spatial decorrelation model. The primary objectives of this study are to determine the accuracy of the NDGPS for the typical user and the development of an updated spatial decorrelation model for performance as a function of distance from the NDPGS reference site (the current model from the 1993 Broadcast Standard, is 2 meters plus 1 meter per 150 km from the beacon site). Simulation, software processing of existing GPS data sets (available from the Continuously Operating Reference Station or CORS, network) at a collection of spatially dispersed sites with the same NDGPS corrections, and actual field measurements at selected sites provides data for these objectives. This current paper provides results from all testing to date

One of the promising opportunities of digital health is its potential to lead to more holistic un... more One of the promising opportunities of digital health is its potential to lead to more holistic understandings of diseases by interacting with the daily life of patients and through the collection of large amounts of real world data. Validating and benchmarking indicators of disease severity in the home setting is difficult, however, given the large number of confounders present in the real world and the challenges in collecting ground truth data in the home. Here we leverage two datasets with continuous wrist-worn accelerometer data coupled with frequent symptom reports in the home setting, to develop digital biomarkers of symptom severity. Using these data, we performed a public benchmarking challenge in which participants were asked to build measures of severity across 3 symptoms (on/off medication, dyskinesia, and tremor). 42 teams participated and performance was improved over baseline models for each subchallenge. Additional ensemble modeling across submissions further improved...

Annals of Noninvasive Electrocardiology, 2021

Atrial fibrillation (AF) is the most common arrhythmia, and despite progress with catheter ablati... more Atrial fibrillation (AF) is the most common arrhythmia, and despite progress with catheter ablation and pulmonary vein isolation, there is a need for pharmacological treatment alternatives. Few new pharmacological options have been added during the last decade and there is a need for improved risk markers to avoid pro-arrhythmias (Lafuente-Lafuente et al., 2012).

Circulation: Arrhythmia and Electrophysiology, 2021

This collaborative statement from the International Society for Holter and Noninvasive Electrocar... more This collaborative statement from the International Society for Holter and Noninvasive Electrocardiology/Heart Rhythm Society/European Heart Rhythm Association/Asia-Pacific Heart Rhythm Society describes the current status of mobile health technologies in arrhythmia management. The range of digital medical tools and heart rhythm disorders that they may be applied to and clinical decisions that may be enabled are discussed. The facilitation of comorbidity and lifestyle management (increasingly recognized to play a role in heart rhythm disorders) and patient self-management are novel aspects of mobile health. The promises of predictive analytics but also operational challenges in embedding mobile health into routine clinical care are explored.

Annals of Noninvasive Electrocardiology, 2021

This collaborative statement from the International Society for Holter and Noninvasive Electrocar... more This collaborative statement from the International Society for Holter and Noninvasive Electrocardiology/Heart Rhythm Society/European Heart Rhythm Association/Asia Pacific Heart Rhythm Society describes the current status of mobile health ("mHealth") technologies in arrhythmia management. The range of digital medical tools and heart rhythm disorders that they may be applied to and clinical decisions that may be enabled are discussed. The facilitation of comorbidity and lifestyle management (increasingly recognized to play a role in heart rhythm disorders) and patient self-management are novel aspects of mHealth. The promises of predictive analytics but also operational challenges in embedding mHealth into routine clinical care are explored.

Journal of Electrocardiology, 2017

The increasing dissemination of wearable ECG recorders (e.g. Holter, patches, and strap sensors) ... more The increasing dissemination of wearable ECG recorders (e.g. Holter, patches, and strap sensors) enables the acquisition of large amounts of data during long periods of time. However, the clinical value of these long-term continuous recordings is hindered by the lack of automatic tools to extract clinically relevant information (other than non-sinus and lifethreatening rhythms) from such long-term data, particularly when targeting population-based research. In this work, we propose and test a new tool for analyzing beat-to-beat interval measurements and extracting features from Holter ECGs. Specifically, we assess the adaptation of the QT interval following sudden changes in heart rate in the primary long QT types (1 & 2). We find that in long QT syndrome type 2, certain QT adaptation patterns can indicate a higher risk for cardiac events.

Journal of Electrocardiology, 2017

Interest in the effects of drugs on the heart rate-corrected JTpeak (JTpc) interval from the body... more Interest in the effects of drugs on the heart rate-corrected JTpeak (JTpc) interval from the body-surface ECG has spawned an increasing number of scientific investigations in the field of regulatory sciences, and more specifically in the context of the Comprehensive in vitro Proarrhythmia Assay (CiPA) initiative. We conducted a novel initiative to evaluate the role of automatic JTpc measurement technologies by comparing their ability to distinguish multi-from single-channel blocking drugs. A set of 5,232 ECGs was shared by the FDA (through the Telemetric and Holter ECG Warehouse) with 3 ECG device companies (AMPS, Mortara, and Philips). We evaluated the differences in drug-concentration effects on these measurements between the commercial and the FDA technologies. We provide a description of the druginduced placebo-corrected changes from baseline for dofetilide, quinidine, ranolazine, and verapamil, and discuss the various differences across all technologies. The results revealed only small differences between measurement technologies confirming that the JTpc interval distinguishes between multi-and single-channel (hERG) blocking drugs when evaluating the effects of dofetilide, quinidine, ranolazine, and verapamil. In the case of quinidine and dofetilide, we noticed a poor consistency across technologies because of the lack of standard definitions for the location of the peak of the Twave (T-apex) when the T-wave morphology is abnormal.

Computer, 2016

Portable medical devices generate volumes of data that could be useful in identifying health risk... more Portable medical devices generate volumes of data that could be useful in identifying health risks. The proposed method filters patients' electrocardiograms (ECGs) and applies machine-learning classifiers to identify cardiac health risks and estimate severity. The authors present the results of applying their method in a case study.

2016 IEEE Symposium on Computers and Communication (ISCC), 2016

The past few decades have witnessed incredible advances in human health care, owing to the invent... more The past few decades have witnessed incredible advances in human health care, owing to the invention of devices such as MRI scanners, which allow physicians to monitor personal health in more detail than was ever previously possible. Such advances have drastically improved diagnostic quality and patient health care. Central to this incredible progress was the uncanny ability of technologists and academics to invent ever more useful tools to help physicians, be it the X-ray machine, CT, or MRI scanner. Whereas the aforementioned past-decades' tools aimed at acquiring personal data, the advent of the Internetof-Things, vast computational power available in the cloud, and new data analytics algorithms will completely change the way we acquire and process medical data to improve health care going forward. In this paper, we conduct a quantitative feasibility study of a Digital Health (D-Health) system that is aimed at acquiring and processing health data using the emerging Internet-of-Everything paradigm. We specifically investigate the technological feasibility of communication, software, and data privacy aspects.

2015 IEEE Global Communications Conference (GLOBECOM), 2014

As global healthcare systems transition into the digital era, remote patient health monitoring wi... more As global healthcare systems transition into the digital era, remote patient health monitoring will be widespread through the use of inexpensive monitoring devices, such as ECG patches, glucose monitors, etc. Once a sensor-concentratorcloudlet-cloud infrastructure is in place, it is not unrealistic to imagine a scenario where a physician monitors 20-30 patients remotely. Such an infrastructure will revolutionize clinical diagnostics and preventative medicine by allowing the doctors to access long-term and real-time information, which cannot be obtained from short-term in-hospital ECG recordings. While the large amount of sensor data available to a physician is incredibly valuable clinically, it is overwhelming in raw form. In this paper, the data handling aspect of such a long term health monitoring system is studied. Novel ways to record, aggregate, and visualize this flood of sensory data in an intuitive manner are introduced which allow a doctor to review days worth of data in a matter of seconds. This system is one of the first attempts to provide a tool that allows the visualization of longterm monitoring data acquired from multiple sensors.

IEEE Access, 2015

The collection of long term health data is accelerating with the advent of portable/wearable medi... more The collection of long term health data is accelerating with the advent of portable/wearable medical devices including electrocardiograms (ECGs). This large corpus of data presents great opportunities to improve the quality of cardiac care. However, analyzing the data from these sensors is a challenge; the relevant information from ∼120,000 heart beats per patient per day must be condensed into a human-readable form. Our goal is to facilitate the analysis of these unwieldy data sets. Methods: We have developed an open source tool for creating easy-to-interpret plots of cardiac information over long periods. We call these plots "ECG Clocks." The utility of our ECG Clock library is demonstrated through multiple examples drawn from a database of 24-hour Holter recordings. In these case studies, we focus on visualization of heart rate and QT dynamics. Results: The ECG Clock concept is shown to be relevant for both physicians and researchers, for identifying healthy and abnormal values and patterns in ECG recordings. Conclusion: In this paper, we describe how to use the ECG Clock library to analyze 24-hour ECG recordings, and how to extend the source code for your own purposes. The tool is applicable to a wide range of cardiac monitoring tasks, such as heart rate variability or ST elevation. Significance: This library, which we have made freely available, can help provide new insights into circadian patterns of cardiac function in individuals and groups.

Enabling Real-Time Mobile Cloud Computing through Emerging Technologies

In today's technology, even leading medical institutions diagnose their cardiac patients thro... more In today's technology, even leading medical institutions diagnose their cardiac patients through ECG recordings obtained at healthcare organizations (HCO), which are costly to obtain and may miss significant clinically-relevant information. Existing long-term patient monitoring systems (e.g., Holter monitors) provide limited information about the evolution of deadly cardiac conditions and lack interactivity in case there is a sudden degradation in the patient's health condition. A standardized and scalable system does not currently exist to monitor an expanding set of patient vitals that a doctor can prescribe to monitor. The design of such a system will translate to significant healthcare savings as well as drastic improvements in diagnostic accuracy. In this chapter, we will propose a concept system for real-time remote cardiac health monitoring, based on available and emerging technologies today. We will analyze the details of such a system from acquisition to visualizati...