Remote Activity Monitoring Research Articles

Using heart rate data from wrist worn activity trackers to define thresholds for moderate to vigorous physical activity in children and young people with cystic fibrosis

BackgroundChildren and young people with cystic fibrosis (CYPwCF) are encouraged to do an average of 60 min of moderate-to-vigorous physical activity (MVPA) daily. However, there are no agreed heart rate (HR) thresholds for defining MVPA, so it is difficult to ascertain whether these targets are actually achieved. Wearable activity trackers enable continuous monitoring of fitness-related measures such as HR and could be used to measure duration and intensity of habitual MVPA. We aimed to define personalized and responsive MVPA thresholds from HR in CYPwCF, to determine habitual time spent in MVPA during childhood and adolescence. MethodsContinuous daily HR data were collected from 142 CYPwCF wearing activity trackers over 16 months. Linear mixed-effects models were used to develop personalised estimates of resting heart rate (RHR), peak heart rate (PHR) and MVPA thresholds, which were defined using the American College of Sports Medicine heart rate reserve (HRR) method. Results309,926 days of physical activity data showed that both RHR and PHR declined with age in CYPwCF, with considerable variability within and between individuals. The HRR method produced personalised MVPA thresholds for each CYPwCF based on age, which inherently accounted for individual demographic variability and personal factors such as cardiovascular fitness or disease severity. ConclusionsBy accounting for within and between person variability in RHR and PHR, our novel method provides more accurate age-related personalised MVPA thresholds for CYPwCF than existing estimates. Our findings provide population-based estimates for RHR, PHR and MVPA thresholds at different ages in CYPwCF. This approach may help guide development of international standards for objective MVPA measurement in the era of remote HR and activity monitoring and facilitate accurate measurement of habitual physical activity in children and young people.

Assessment of Wearable Device Adherence for Monitoring Physical Activity in Older Adults: Pilot Cohort Study.

Physical activity has emerged as a modifiable behavioral factor to improve cognitive function. However, research on adherence to remote monitoring of physical activity in older adults is limited. This study aimed to assess adherence to remote monitoring of physical activity in older adults within a pilot cohort from objective user data, providing insights for the scalability of such monitoring approaches in larger, more comprehensive future studies. This study included 22 participants from the Boston University Alzheimer's Disease Research Center Clinical Core. These participants opted into wearing the Verisense watch as part of their everyday routine during 14-day intervals every 3 months. Eighteen continuous physical activity measures were assessed. Adherence was quantified daily and cumulatively across the follow-up period. The coefficient of variation was used as a key metric to assess data consistency across participants over multiple days. Day-to-day variability was estimated by calculating intraclass correlation coefficients using a 2-way random-effects model for the baseline, second, and third days. Adherence to the study on a daily basis outperformed cumulative adherence levels. The median proportion of adherence days (wearing time surpassed 90% of the day) stood at 92.1%, with an IQR spanning from 86.9% to 98.4%. However, at the cumulative level, 32% (7/22) of participants in this study exhibited lower adherence, with the device worn on fewer than 4 days within the requested initial 14-day period. Five physical activity measures have high variability for some participants. Consistent activity data for 4 physical activity measures might be attainable with just a 3-day period of device use. This study revealed that while older adults generally showed high daily adherence to the wearable device, consistent usage across consecutive days proved difficult. These findings underline the effectiveness of wearables in monitoring physical activity in older populations and emphasize the ongoing necessity to simplify usage protocols and enhance user engagement to guarantee the collection of precise and comprehensive data.

Remote Continuous Monitoring of Tree Physiological Activity using Four-point Electrical Resistance Measurement

Remote Continuous Monitoring of Tree Physiological Activity using Four-point Electrical Resistance Measurement

Remote monitoring of physical activity in individuals with Acquired Brain Injury

Remote monitoring of physical activity in individuals with Acquired Brain Injury

Portable ECG monitoring system with IOT analysis

This system is designed to calculate the heart rate of patients and transmit the data in beats per minute (bpm) to a cloud database. By using this system, doctors can analyze critical parameters remotely. The project involves interfacing the AD8232 ECG Sensor with the NodeMCU ESP8266 Board to monitor ECG waveforms on a Serial Plotter Screen and transmit the data to an IoT cloud platform for real-time monitoring. This innovation allows for remote monitoring of heart activity, reducing the need for hospital stays. Utilizing the Blynk IoT platform, the system ensures online access via PC or Smartphone, representing a significant advancement in patient health monitoring. This approach aims to improve early detection and prevention of heart diseases, enhancing patient care and reducing fatalities.

Implementing a Clinical Decision Support Tool to Improve Physical Activity.

Currently, only about half of U.S. adults achieve current physical activity guidelines. Routine physical activity is not regularly assessed, nor are patients routinely counseled by their healthcare provider on achieving recommended levels. The three-question physical activity vital sign (PAVS) was developed to assess physical activity duration and intensity and identify adults not meeting physical activity guidelines. Clinical decision support provided via a best practice advisory in an electronic health record (EHR) system can be triggered as a prompt, reminding healthcare providers to implement the best practice intervention when appropriate. Remote patient monitoring of physical activity can provide objective data in the EHR. This study aimed to evaluate the feasibility and clinical utility of embedding the PAVS and a triggered best practice advisor into the EHR in an ambulatory preventive cardiology practice setting to alert providers to patients reporting low physical activity and prompt healthcare providers to counsel these patients as needed. Three components based in the EHR were integrated for the purpose of this study: Patients completed the PAVS through their electronic patient portal prior to an office visit, a best practice advisory was created to prompt providers to counsel patients who reported low levels of physical activity, and remote patient monitoring via Fitbit synced to the EHR provided objective physical activity data. The intervention was pilot-tested in the Epic EHR for 1 year (July 1, 2021 to June 30, 2022). Qualitative feedback on the intervention from both providers and patients was obtained at the completion of the study. Monthly assessments of the use of the PAVS and best practice advisory and remote patient monitoring were completed. Patients' completion of the PAVS varied from 35% to 48% per month. The best practice advisory was signed by providers between 2% and 65% and was acknowledged by 2%-22% per month. The majority (58%) of patients were able to sync a Fitbit device to their EHR for remote monitoring. Although uptake of each component needs improvement, this pilot demonstrated the feasibility of incorporating a physical activity promotion intervention into the EHR. Qualitative feedback provided guidance for future implementation.

CAN WE USE SMARTPHONES TO MONITOR ORTHOPAEDIC PATIENTS' PHYSICAL ACTIVITIES DURING THE PERIOPERATIVE PERIOD? A PROSPECTIVE OBSERVATIONAL STUDY

Smartphones are often equipped with inertial sensors capable of measuring individuals' physical activities. Their role in monitoring the patients' physical activities in telemedicine, however, needs to be explored. The main objective of this study was to explore the correlation between a participant's daily step counts and the daily step counts reported by their smartphone. This prospective observational study was conducted on patients undergoing lower limb orthopedic surgery and a group of non-patients. The data collection period was from 2 weeks before until four weeks after the surgery for the patients and two weeks for the non-patients. The participants' daily steps were recorded by physical activity trackers employed 24/7, and an application recorded the number of daily steps registered by the participants' smartphones. We compared the cross-correlation between the daily steps time-series taken from the smartphones and physical activity trackers in different groups of participants. We also employed mixed modeling to estimate the total number of steps. Overall, 1067 days of data were collected from 21 patients (11 females) and 10 non-patients (6 females). The cross-correlation coefficient between the smartphone and physical activity tracker was 0.70 [0.53–0.83]. The correlation in the non-patients was slightly higher than in the patients (0.74 [0.60–0.90] and 0.69 [0.52–0.81], respectively). Considering the ubiquity, convenience, and practicality of smartphones, the high correlation between the smartphones and the total daily step time-series highlights the potential usefulness of smartphones in detecting the change in the step counts in remote monitoring of the patient's physical activity.

Supporting Community First Responders in Aging in Place: An Action Design for a Community-Based Smart Activity Monitoring System

To maintain elderly individuals’ ability to live independently in their own homes, technologies such as sensors and the Internet of Things can be used to facilitate real-time monitoring and automate emergency detection and alerts to enable first responders to deliver help on time. This study examines the design problems associated with such activity monitoring systems, particularly how to support the situational awareness of community first responders who are located remotely and do not have professional healthcare knowledge. Based on a three-year action design research study that investigated a sensor-based monitoring system for elderly people deployed in a natural community setting, we develop abstract design knowledge. Four design principles aimed at enhancing responders’ perceptions, comprehension, and projection of information are proposed to promote informed decision-making and timely responses by drawing on the situational awareness model. In addition to the nascent design knowledge regarding remote activity monitoring in different instances, this study extends our knowledge of the community-based model by foregrounding its multiplicity and the active roles of community stakeholders in providing care to elderly people.

A stand-alone proximity-based gaming wearable for remote physical activity monitoring

Abstract The Internet of Things (IoT) and wearable computing are crucial elements of modern information systems and applications in which advanced features for user interactivity and monitoring are required. However, in the fields of pervasive gaming, IoT has had limited real-world applications. In this work, we present a prototype of a wearable platform for pervasive games that combines IoT with wearable computing to enable the real-time monitoring of physical activity. The main objective of the solution is to promote the utilization of gamification techniques to enhance the physical activity of users through challenges and quests. This aims to create a symbolic link between the virtual gameplay and the real-world environment without the requirement of a smartphone. With the integration of sensors and wearable devices by design, the platform has the capability of real-time monitoring the users’ physical activity during the game. The system performance results highlight the efficiency and attractiveness of the wearable platform for gamifying physical activity.

Follow-Up of Patients With Axial Spondyloarthritis in Specialist Health Care With Remote Monitoring and Self-Monitoring Compared With Regular Face-to-Face Follow-Up Visits (the ReMonit Study): Protocol for a Randomized, Controlled Open-Label Noninferiority Trial.

Patients with chronic inflammatory joint diseases such as axial spondyloarthritis have traditionally received regular follow-up in specialist health care to maintain low disease activity. The follow-up has been organized as prescheduled face-to-face visits, which are time-consuming for both patients and health care professionals. Technology has enabled the remote monitoring of disease activity, allowing patients to self-monitor their disease and contact health care professionals when needed. Remote monitoring or self-monitoring may provide a more personalized follow-up, but there is limited research on how these follow-up strategies perform in maintaining low disease activity, patient satisfaction, safety, and cost-effectiveness. The Remote Monitoring in Axial Spondyloarthritis (ReMonit) study aimed to assess the effectiveness of digital remote monitoring and self-monitoring in maintaining low disease activity in patients with axial spondyloarthritis. The ReMonit study is a 3-armed, single-site, randomized, controlled, open-label noninferiority trial including patients with axial spondyloarthritis with low disease activity (Ankylosing Spondylitis Disease Activity Score <2.1) and on stable treatment with a tumor necrosis factor inhibitor. Participants were randomized 1:1:1 to arm A (usual care, face-to-face visits every sixth month), arm B (remote monitoring, monthly digital registration of patient-reported outcomes), or arm C (patient-initiated care, self-monitoring, no planned visits during the study period). The primary end point was disease activity measured with the Ankylosing Spondylitis Disease Activity Score, evaluated at 6, 12, and 18 months. We aimed to include 240 patients, 80 in each arm. Secondary end points included other measures of disease activity, patient satisfaction, safety, and cost-effectiveness. The project is funded by the South-Eastern Norway Regional Health Authority and Centre for the treatment of Rheumatic and Musculoskeletal Diseases (REMEDY), Diakonhjemmet Hospital, Norway. Enrollment started in September 2021 and was completed with 242 patients by June 2022. The data collection will be completed in December 2023. To our knowledge, this trial will be among the first to evaluate the effectiveness, safety, and cost-effectiveness of remote digital monitoring and self-monitoring of patients with axial spondyloarthritis compared with usual care. Hence, the ReMonit study will contribute important knowledge to personalized follow-up strategies for patients with axial spondyloarthritis. These results may also be relevant for other patient groups with inflammatory joint diseases. ClinicalTrials.gov NCT05031767; hpps://www.clinicaltrials.gov/study/NCT05031767. DERR1-10.2196/52872.

Abstract PR005: Preferences of older cancer survivors for integration of remote activity monitoring using wearable devices

Abstract Purpose: To describe the preferences for integration of wearable devices into their healthcare to remotely monitor physical activity among older adult cancer survivors. Methods: 89 cancer survivors, aged 65 and older, completed our preferences for wearable devices in healthcare questionnaire. Participants were asked to self-report demographic information, current physical activity participation, and preferences for inclusion of wearable devices as part of their care plan through a current provider (i.e. physician, physical therapist, etc.). Data are summarized and reported as mean ± standard deviation or percent. Results: Participants were on average 71±5 years old, 59% female, and mostly White, non-Hispanic (93%). 76.2% of participants reporting engaging in 0 days of vigorous intensity physical activity, with 31% reporting no moderate intensity physical activity. 59% of older cancer survivors report they already own a wearable device, with the most common device being a wrist-worn device (93%). For those that do not currently own a device, 94% report they would be interested in owning a wearable device. 94% of older cancer survivors state they would be interested in using a wearable device as part of their usual care plan for their provider to remotely monitor their health. 88% report having no privacy concerns with sharing their wearable data with their healthcare provider. Participants report they would be willing to purchase their own monitor if it meant future out of pocket healthcare costs (81%) or reduced time investment to travel to the clinic (63%). Conclusions: Results indicate older cancer survivors are interested in their care team remotely monitoring their activity levels. Further, the majority of older cancer survivors report they are willing to purchase their own device. Future research is warranted to determine an implementation plan to integrate these devices into current clinic workflows and determine optimal interaction among patients and providers. Citation Format: Whitney A. Morelli, Kelly Clohesey, Jessica Liu. Preferences of older cancer survivors for integration of remote activity monitoring using wearable devices [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr PR005.

Implementing Remote Patient Monitoring of Physical Activity in Clinical Practice

Implementing Remote Patient Monitoring of Physical Activity in Clinical Practice

Implementing Remote Patient Monitoring of Physical Activity in Clinical Practice.

Remote patient monitoring (RPM) is a tool for patients to share data collected outside of office visits. RPM uses technology and the digital transmission of data to inform clinician decision-making in patient care. Using RPM to track routine physical activity is feasible to operationalize, given contemporary consumer-grade devices that can sync to the electronic health record. Objective monitoring through RPM can be more reliable than patient self-reporting for physical activity. This article reports on four pilot studies that highlight the utility and practicality of RPM for physical activity monitoring in outpatient clinical care. Settings include endocrinology, cardiology, neurology, and pulmonology settings. The four pilot use cases discussed demonstrate how RPM is utilized to monitor physical activity, a shift that has broad implications for prediction, prevention, diagnosis, and management of chronic disease and rehabilitation progress. If RPM for physical activity is to be expanded, it will be important to consider that certain populations may face challenges when accessing digital health services. RPM technology provides an opportunity for clinicians to obtain objective feedback for monitoring progress of patients in rehabilitation settings. Nurses working in rehabilitation settings may need to provide additional patient education and support to improve uptake.

Usability and ease of use of long-term remote monitoring of physical activity for individuals with acquired brain injury in community: a qualitative analysis.

Objective and continuous monitoring of physical activity over the long-term in the community is perhaps the most important step in the paradigm shift toward evidence-based practice and personalized therapy for successful community integration. With the advancement in technology, physical activity monitors have become the go-to tools for objective and continuous monitoring of everyday physical activity in the community. While these devices are widely used in many patient populations, their use in individuals with acquired brain injury is slowly gaining traction. The first step before using activity monitors in this population is to understand the patient perspective on usability and ease of use of physical activity monitors at different wear locations. However, there are no studies that have looked at the feasibility and patient perspectives on long-term utilization of activity monitors in individuals with acquired brain injury. This pilot study aims to fill this gap and understand patient-reported aspects of the feasibility of using physical activity monitors for long-term use in community-dwelling individuals with acquired brain injury. This pilot study found that patients with acquired brain injury faced challenges specific to their functional limitations and that the activity monitors worn on the waist or wrist may be better suited in this population. The unique wear location-specific challenges faced by individuals with ABI need to be taken into account when selecting wearable activity monitors for long term use in this population.

Audio-Conversion of Biomedical Signals - A Possible Approach to Improve Remote Monitoring of Elderly and Visually Impaired People.

Long-term remote patients monitoring implies minimal discomfort and reliability throughout the study period. These requirements are fulfilled by portable (wearable) patient devices, with low consumption, which transmit data wirelessly, at a short distance, to a mobile communication device (GSM) and through it, to a remote end recipient - doctor, medical center or a hospital server. The data transfer technology requires the monitored person to perform a sequence of actions, such as: selecting the appropriate application on the mobile phone, establishing a connection between the patient module and the phone, recording the data in the phone's memory, starting the data transfer from the phone to the final receiver. Practice shows that often this sequence of activities is difficult for elderly people and especially for visually impaired people, which as a result compromises the remote monitoring process. In this paper are presented an approach and conceptual implementation of a system for remote monitoring of cardiac activity, using the most popular way of remote connectivity - voice (sound) communication. In addition to the ease of use, this type of communication does not require special data protection, due to the lack of RF interfaces for short-distance data transmission. The presented results of laboratory studies, as well as conducted tests under medical supervision of patients in a cardiology clinic, confirm the workability of the proposed approach for remote monitoring of patients by audio conversion of the ECG signal.

Non-contact heart vibration measurement using computer vision-based seismocardiography

Seismocardiography (SCG) is the noninvasive measurement of local vibrations of the chest wall produced by the mechanical activity of the heart and has shown promise in providing clinical information for certain cardiovascular diseases including heart failure and ischemia. Conventionally, SCG signals are recorded by placing an accelerometer on the chest. In this paper, we propose a novel contactless SCG measurement method to extract them from chest videos recorded by a smartphone. Our pipeline consists of computer vision methods including the Lucas–Kanade template tracking to track an artificial target attached to the chest, and then estimate the SCG signals from the tracked displacements. We evaluated our pipeline on 14 healthy subjects by comparing the vision-based SCG^mathrm{{v}} estimations with the gold-standard SCG^mathrm{{g}} measured simultaneously using accelerometers attached to the chest. The similarity between SCG^mathrm{{g}} and SCG^mathrm{{v}} was measured in the time and frequency domains using the Pearson correlation coefficient, a similarity index based on dynamic time warping (DTW), and wavelet coherence. The average DTW-based similarity index between the signals was 0.94 and 0.95 in the right-to-left and head-to-foot directions, respectively. Furthermore, SCG^mathrm{{v}} signals were utilized to estimate the heart rate, and these results were compared to the gold-standard heart rate obtained from ECG signals. The findings indicated a good agreement between the estimated heart rate values and the gold-standard measurements (bias = 0.649 beats/min). In conclusion, this work shows promise in developing a low-cost and widely available method for remote monitoring of cardiovascular activity using smartphone videos.

Exploring the feasibility and usability of smartphones for monitoring physical activity in orthopedic patients: A prospective observational study.

Smartphones are often equipped with inertial sensors that measure individuals' physical activities. However, their role in remote monitoring of the patients' physical activities in telemedicine needs to be adequately explored. The main objective of this study was to explore the correlation between a participant's actual daily step counts and the daily step counts reported by their smartphone. In addition, we inquired about the usability of using smartphones for collecting physical activity data. This prospective observational study was conducted on patients undergoing lower limb orthopedic surgery and a group of non-patients as control. The data from the patients were collected from 2 weeks before surgery until four weeks after the surgery, while the data collection period for the non-patients was two weeks. The participant's daily step count was recorded by physical activity trackers employed 24/7. In addition, a smartphone application collected the number of daily steps registered by the participants' smartphones. We compared the cross-correlation between the daily steps time-series taken from the smartphones and physical activity trackers in different groups of participants. We also employed mixed modeling to estimate the total number of steps, using smartphone step counts and the characteristics of the patients as independent variables. The System Usability Scale was used to evaluate the participants' experience with the smartphone application and the physical activity tracker. Overall, 1067 days of data were collected from 21 patients (11 females) and 10 non-patients (6 females). The median and IQR for the cross-correlation coefficient on the same day was 0.70 [0.53-0.83]. The correlation in the non-patients was slightly higher than in the patients (0.74 [0.60-0.90] and 0.69 [0.52-0.81], respectively). The likelihood ratio tests on the models fitted by mixed effect methods demonstrated that the smartphone step count was positively correlated with the physical activity tracker's total number of steps (χ2 = 34.7, p < .00001). In addition, the usability score for the smartphone app was 78 [73-88] compared to 73 [68-80] for the PA tracker. Considering the ubiquity, convenience, and practicality of smartphones, the high correlation between the smartphones and the total daily step count time-series highlights the potential usefulness of smartphones in detecting the change in the number of steps in remote monitoring of the patient's physical activity.

Automated Sampling System for Monitoring 85Kr in Air

Radioactive krypton-85 (85Kr) gas, a chemically inert and non-proliferation indicator, is derived from fission products. Its detection relies on the Budesamt für Strahlenschutz–Institute of Atmospheric Radioactivity (BfS-IAR) method, which necessitated impurity removal using soda lime, silica gel, and liquid nitrogen for cryogenic adsorption. This manual process requires frequent replacements, posing challenges for its automation. To address this, we developed a prototype krypton sampling system as an interim research product for the fully automated remote monitoring of covert nuclear activity. The system incorporates a hollow fiber membrane for impurity removal, a computer-controlled multi-position valve for sampling, and an electric cooler for adsorption. The impurity removal modules demonstrated high efficiencies, removing H2O and CO2 at 99.8% and 97.8% rates, respectively. Further, the custom-made sampling system can process 16 samples in a single run without analyst intervention. We conducted experiments to verify the automatic krypton sampling capability. The activity concentration of 85Kr in ambient air was measured using the BfS-IAR processing and detection system. The system exhibited a recovery rate of ~7.8% for krypton in 1000 L air, demonstrating good continuous remote monitoring capability. This study promotes the development of an automated analysis system for the detection of 85Kr in ambient air.

Remote Patient Activity Monitoring System by Integrating IoT Sensors and Artificial Intelligence Techniques.

Even with the most cutting-edge tools, treating and monitoring patients-including children, elders, and suspected COVID-19 patients-remains a challenging activity. This study aimed to track multiple COVID-19-related vital indicators using a wearable monitoring device with an Internet of Things (IOT) focus. Additionally, the technology automatically alerts the appropriate medical authorities about any breaches of confinement for potentially contagious patients by tracking patients' real-time GPS data. The wearable sensor is connected to a network edge in the Internet of Things cloud, where data are processed and analyzed to ascertain the state of body function. The proposed system is built with three tiers of functionalities: a cloud layer using an Application Peripheral Interface (API) for mobile devices, a layer of wearable IOT sensors, and a layer of Android web for mobile devices. Each layer performs a certain purpose. Data from the IoT perception layer are initially collected in order to identify the ailments. The following layer is used to store the information in the cloud database for preventative actions, notifications, and quick reactions. The Android mobile application layer notifies and alerts the families of the potentially impacted patients. In order to recognize human activities, this work suggests a novel integrated deep neural network model called CNN-UUGRU which mixes convolutional and updated gated recurrent subunits. The efficiency of this model, which was successfully evaluated on the Kaggle dataset, is significantly higher than that of other cutting-edge deep neural models and it surpassed existing products in local and public datasets, achieving accuracy of 97.7%, precision of 96.8%, and an F-measure of 97.75%.

Association of Daily Physical Activity with Cervical Spinal Cord Areas in Multiple Sclerosis

Background and purpose Remote activity monitoring has the potential to evaluate real-world motor function and disability outside of the clinic. The relationships of daily physical activity with spinal cord white matter and grey matter areas, MS disability, and leg function are unknown. Our purpose was to evaluate the association of remotely captured ambulatory activity with structural central nervous system pathology via quantitative magnetic imaging, in people with multiple sclerosis (MS). Methods Fifty adults with progressive or relapsing MS with motor disability who could walk at least 2 minutes, were assessed using clinical, patient-reported, and quantitative brain and spinal cord MRI measures. Fitbit Flex2, worn on the non-dominant wrist, remotely assessed activity over 30 consecutive days. Univariate and multivariate analyses were performed to assess correlations between remote physical activity and other disability metrics. Results The mean age of the cohort was 53.3 years and the median EDSS was 4.0. Average daily step counts (STEPS) were highly correlated with EDSS and walking measures (i.e., Timed 25-foot Walk, Timed up and Go tests, and subjective 12- item MS Walking Scale). Greater STEPS correlated with greater C2-C3 spinal cord grey matter areas (rho=0.39, p=0.04), total cord area (rho=0.35, p=0.04), and brain volume (rho=0.32, p=0.04). Discussion These results provide preliminary evidence that spinal cord grey matter area is a neuroanatomical substrate associated with STEPS. STEPS could serve as a proxy to alert clinicians and researchers to possible changes in structural nervous system pathology. Longitudinal observations are needed to determine directionality and value of STEPS as a proxy for generalized brain and cord volume loss. These results have potential implications for structural and functional modification of disease progression via therapeutic interventions aimed at altering STEPS. Remote activity monitoring has the potential to evaluate real-world motor function and disability outside of the clinic. The relationships of daily physical activity with spinal cord white matter and grey matter areas, MS disability, and leg function are unknown. Our purpose was to evaluate the association of remotely captured ambulatory activity with structural central nervous system pathology via quantitative magnetic imaging, in people with multiple sclerosis (MS). Fifty adults with progressive or relapsing MS with motor disability who could walk at least 2 minutes, were assessed using clinical, patient-reported, and quantitative brain and spinal cord MRI measures. Fitbit Flex2, worn on the non-dominant wrist, remotely assessed activity over 30 consecutive days. Univariate and multivariate analyses were performed to assess correlations between remote physical activity and other disability metrics. The mean age of the cohort was 53.3 years and the median EDSS was 4.0. Average daily step counts (STEPS) were highly correlated with EDSS and walking measures (i.e., Timed 25-foot Walk, Timed up and Go tests, and subjective 12- item MS Walking Scale). Greater STEPS correlated with greater C2-C3 spinal cord grey matter areas (rho=0.39, p=0.04), total cord area (rho=0.35, p=0.04), and brain volume (rho=0.32, p=0.04). These results provide preliminary evidence that spinal cord grey matter area is a neuroanatomical substrate associated with STEPS. STEPS could serve as a proxy to alert clinicians and researchers to possible changes in structural nervous system pathology. Longitudinal observations are needed to determine directionality and value of STEPS as a proxy for generalized brain and cord volume loss. These results have potential implications for structural and functional modification of disease progression via therapeutic interventions aimed at altering STEPS.