The promise of wearable activity sensors to define patient recovery

A Retrospective Study on the Feasibility of Using Low-burden Patient-reported Pain Scores to Track Recovery and Outcomes After Total Joint Replacement

Background

Patients undergo total joint arthroplasty to improve function and resolve pain. Patient-reported outcome measures (PROMs) are often sought to determine the success of total joint arthroplasty but are time-consuming and patient response rates are often low. This study sought to determine whether pain numeric rating scores (NRSs) were associated with PROMs and objective mobility outcomes.

Methods

This is a retrospective review of data in patients who utilized a smartphone-based care management application prior to and following total joint arthroplasty. NRS, Hip Disability and Osteoarthritis Outcome Score, Joint Replacement and Knee Injury and Osteoarthritis Outcome Score, Joint Replacement, and objective mobility data (step counts, gait speed, and gait asymmetry) were collected preoperatively and at 30 and 90 days postoperatively. Quantile regression was performed to evaluate the correlations between NRS and PROMs.

Results

Total knee arthroplasty patients reported higher NRS than total hip arthroplasty patients postoperatively. NRS was significantly correlated with gait speed preoperatively and at 30 and 90 days postoperatively on quantile regression. Gait asymmetry was significantly associated with NRS at 30 days postoperatively. Regression results suggested significant correlations between NRS and PROMs scores; Hip Disability and Osteoarthritis Outcome Score, Joint Replacement, -0.46 (95% confidence interval: -0.48 to -0.44, P < .001) and Knee Injury and Osteoarthritis Outcome Score, Joint Replacement, -0.38 (95% confidence interval: -0.40 to -0.36, P < .001).

Conclusions

NRS is correlated with both objective and subjective measures of function in patients undergoing arthroplasty. Simple pain ratings may be a valid measurement to help predict functional outcomes when collection of traditional PROMs is not feasible.

Systems of Care Delivery and Optimization in the Postoperative Care Wards

A third of all patients are at risk for a serious adverse event, including death, in the first month after undergoing a major surgery. Most of these events will occur within 24 hours of the operation but are unlikely to occur in the operating room or postanesthesia care unit. Most opioid-induced respiratory depression events in the postoperative period resulted in death (55%) or anoxic brain injury (22%). A future state of mature artificial intelligence and machine learning will improve situational awareness of acute clinical deterioration, minimize alert fatigue, and facilitate early intervention to minimize poor outcomes.

Reducing endocrine metabolic disease risk in adults with chronic spinal cord injury: strategic activities conducted by the Ontario-Quebec RIISC team

PURPOSE

The Rehabilitation Interventions for Individuals with a Spinal Cord Injury in the Community (RIISC) team aimed to develop and evaluate innovative rehabilitation interventions to identify endocrine metabolic disease (EMD) risk, intending to reduce the frequency and severity of EMD related morbidity and mortality among adults living with chronic spinal cord injury or disease (SCI/D).

MATERIALS AND METHODS

An interprovincial team from Ontario and Quebec reviewed available EMD literature and evidence syntheses and completed an inventory of health services, policies and practices in SCI/D care. The review outcomes were combined with expert opinion to create an EMD risk model to inform health service transformation.

RESULTS

EMD risk and mortality are highly prevalent among adults with chronic SCI/D. In stark contrast, few rehabilitation interventions target EMD outcomes. The modelled solution proposes: 1) abandoning single-disease paradigms and examining a holistic perspective of the individual's EMD risk, and 2) developing and disseminating practice-based research approaches in outpatient community settings.

CONCLUSIONS

RIISC model adoption could accelerate EMD care optimization, and ultimately inform the design of large-scale longitudinal pragmatic trials likely to improve health outcomes. Linking the RIISC team activities to economic evaluations and policy deliverables will strengthen the relevance and impact among policymakers, health care providers and patients.

Spine patient care with wearable medical technology: state-of-the-art, opportunities, and challenges: a systematic review

BACKGROUND CONTEXT

Healthcare reforms that demand quantitative outcomes and technical innovations have emphasized the use of Disability and Functional Outcome Measurements (DFOMs) to spinal conditions and interventions. Virtual healthcare has become increasingly important following the COVID-19 pandemic and wearable medical devices have proven to be a useful adjunct. Thus, given the advancement of wearable technology, broad adoption of commercial devices (ie, smartwatches, phone applications, and wearable monitors) by the general public, and the growing demand from consumers to take control of their health, the medical industry is now primed to formally incorporate evidence-based wearable device-mediated telehealth into standards of care.

PURPOSE

To (1) identify all wearable devices in the peer-reviewed literature that were used to assess DFOMs in Spine, (2) analyze clinical studies implementing such devices in spine care, and (3) provide clinical commentary on how such devices might be integrated into standards of care.

STUDY DESIGN/SETTING

A systematic review.

METHODS

A comprehensive systematic review was conducted in adherence to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Guidelines (PRISMA) across the following databases: PubMed; MEDLINE; EMBASE (Elsevier); and Scopus. Articles related to wearables systems in spine healthcare were selected. Extracted data was collected as per a predetermined checklist including wearable device type, study design, and clinical indices studied.

RESULTS

Of the 2,646 publications that were initially screened, 55 were extensively analyzed and selected for retrieval. Ultimately 39 publications were identified as being suitable for inclusion based on the relevance of their content to the core objectives of this systematic review. The most relevant studies were included, with a focus on wearables technologies that can be used in patients' home environments.

CONCLUSIONS

Wearable technologies mentioned in this paper have the potential to revolutionize spine healthcare through their ability to collect data continuously and in any environment. In this paper, the vast majority of wearable spine devices rely exclusively on accelerometers. Thus, these metrics provide information about general health rather than specific impairments caused by spinal conditions. As wearable technology becomes more prevalent in orthopedics, healthcare costs may be reduced and patient outcomes will improve. A combination of DFOMs gathered using a wearable device in conjunction with patient-reported outcomes and radiographic measurements will provide a comprehensive evaluation of a spine patient's health and assist the physician with patient-specific treatment decision-making. Establishing these ubiquitous diagnostic capabilities will allow improvement in patient monitoring and help us learn about postoperative recovery and the impact of our interventions.

A Systematic Review of the Use of Commercial Wearable Activity Trackers for Monitoring Recovery in Individuals Undergoing Total Hip Replacement Surgery

The innovation of wearable devices is advancing rapidly. Activity monitors can be used to improve the total hip replacement (THR) patients' recovery process and reduce costs. This systematic review assessed the body-worn accelerometers used in studies to enhance the rehabilitation process and monitor THR patients. Electronic databases such as Cochrane Database of Systematic Reviews library, CINAHL CompleteVR, Science Citation Index, and MedlineVR from January 2000 to January 2022 were searched. Due to inclusion criteria, fourteen eligible studies that utilised commercial wearable technology to monitor physical activity both before and after THR were identified. Their evidence quality was assessed with RoB 2.0 and ROBINS-I. This study demonstrates that wearable device technology might be feasible to predict, monitor, and detect physical activity following THR. They could be used as a motivational tool to increase patients' mobility and enhance the recovery process. Also, wearable activity monitors could provide a better insight into the individual's activity level in contrast to subjective self-reported questionnaires. However, they have some limitations, and further evidence is needed to establish this technology as the primary device in THR rehabilitation.

Monitoring postoperative ambulation and sleep after head and neck surgery: A feasibility and utility study using wearable devices

BACKGROUND

To evaluate use of wearable activity devices to monitor trends in ambulation and sleep after head and neck surgery.

METHODS

Patients utilized Fitbit devices after surgery. Daily activity and sleep scores, step counts, and total sleep time (TST) were obtained.

RESULTS

There were 30 patients within the final cohort. Trends in step counts after specific procedures were identified, and higher subjective activity level correlated with step counts (r = 0.25, 95% CI = 0.07-0.41). Among patients with complete step data (n = 24), POD1 steps ≥200 were associated with reduced length of stay (4.5 ± 1.7 days vs. 7.2 ± 4.0 days, 95% CI = 0.33-5.0). Mean TST was 5.4 ± 2.5 h, TST correlated with subjective sleep scores (r = 0.25, 95% CI = 0.03-0.044), and clinical events associated with sleep-wake transitions on Fitbit devices were identified.

CONCLUSIONS

Wearable activity devices appear feasible for monitoring trends in postoperative ambulation and sleep. Use of these devices may facilitate postoperative recovery.

Feasibility and Prediction of Adverse Events in a Postoperative Monitoring Program of Patient-Reported Outcomes and a Wearable Device Among Gynecologic Oncology Patients

PURPOSE

The objective of this study was to test the feasibility of implementing a postoperative monitoring program for women with gynecologic cancers composed of patient-reported outcomes (PROs) and a wearable activity monitor.

METHODS

We prospectively enrolled patients undergoing gynecologic cancer surgery to this single-arm study. Enrolled patients completed PROs (Patient-Reported Outcomes Measurement Information System physical function, sleep disturbance, anxiety, fatigue, and pain intensity) at baseline and one-week intervals for 4 weeks. They also wore a wearable accelerometer device that measured steps, heart rate, and intensity of physical activity. The primary outcome was feasibility. The secondary outcome was prediction of unscheduled contacts with the health care system on a given postoperative day.

RESULTS

We enrolled 34 women. Three patients were unevaluable. The mean age was 58 years. The mean body mass index was 31 kg/m²; 17 patients were White (54.8%), 12 patients were Black (38.7%), and two patients (6.5%) were Asian. The overall wear time was 83.8%, and patients responded to 80.4% of the PRO instruments. Twenty-two patients (71%) had an unscheduled contact with the health care system postoperatively (median 1.5, 0.0-8.0). The day of an unscheduled health care utilization event was predicted with acceptable discrimination (area under the receiver operating characteristic curve 0.75; 95% CI, 0.67 to 0.81). PROs of fatigue and physical function were most predictive followed by wearable device outputs of lightly active minutes and average daily heart rate.

CONCLUSION

Implementation of a postoperative monitoring program of patient-reported outcomes and a wearable device was feasible. The specific day of an unscheduled contact with the health care system was predicted with acceptable discrimination.

Technical, Regulatory, Economic, and Trust Issues Preventing Successful Integration of Sensors into the Mainstream Consumer Wearables Market

Sensors that track physiological biomarkers of health must be successfully incorporated into a fieldable, wearable device if they are to revolutionize the management of remote patient care and preventative medicine. This perspective article discusses logistical considerations that may impede the process of adapting a body-worn laboratory sensor into a commercial-integrated health monitoring system with a focus on examples from sleep tracking technology.

Remote Health Monitoring in Clinical Trial using Machine Learning Techniques: A Conceptual Framework

Monitoring any process is crucial and very necessary, this is to ensure that standard protocols and procedures are strictly adhered to, monitoring clinical trials is not an exception. It is one of the most crucial processes that should be monitored because human subjects are involved. In trying to monitor clinical trial, information and communication technology techniques can be deployed to facilitate the process and hence improve accuracy. This research formulates a new conceptual framework for monitoring clinical trial using Support Vector Machine and Artificial Neural Network classifiers with physiological datasets from a wearable device. The proposed framework prototype consists of data collection module, data transmission module, and data analysis and prediction module. The data analytic and prediction module is the core section of the proposed framework tailored with data analysis. These datasets are preprocessed and transformed and then used to train and test the system, through different experimental analysis including bagging Support Vector Machine (SVM) and Artificial Neural Network (ANN). The outcome of the analysis presents classification into three different categories, such as fit, unfit, and undecided participants. These various classifications are used to determine if a participant should be allowed to continue in the trial or not. This research provides a framework that is useful in monitoring clinical trial remotely, thereby informing the decision-making process of the research team.

OUP accepted manuscript

Background

Wearable devices have been proposed as a novel method for monitoring patients after surgery to track recovery, identify complications early, and improve surgical safety. Previous studies have used a heterogeneous range of devices, methods, and analyses. This review aimed to examine current methods and wearable devices used for monitoring after abdominal surgery and identify knowledge gaps requiring further investigation.

Methods

A scoping review was conducted given the heterogeneous nature of the evidence. MEDLINE, EMBASE, and Scopus databases were systematically searched. Studies of wearable devices for monitoring of adult patients within 30 days after abdominal surgery were eligible for inclusion.

Results

A total of 78 articles from 65 study cohorts, with 5153 patients were included. Thirty-one different wearable devices were used to measure vital signs, physiological measurements, or physical activity. The duration of postoperative wearable device use ranged from 15 h to 3 months after surgery. Studies mostly focused on physical activity metrics (71.8 per cent). Continuous vital sign measurement and physical activity tracking both showed promise for detecting postoperative complications earlier than usual care, but conclusions were limited by poor device precision, adherence, occurrence of false alarms, data transmission problems, and retrospective data analysis. Devices were generally well accepted by patients, with high levels of acceptance, comfort, and safety.

Conclusion

Wearable technology has not yet realized its potential to improve postoperative monitoring. Further work is needed to overcome technical limitations, improve precision, and reduce false alarms. Prospective assessment of efficacy, using an intention-to-treat approach should be the focus of further studies.

Mobile devices and wearable technology for measuring patient outcomes after surgery: a systematic review

Complications following surgery are common and frequently occur the following discharge. Mobile and wearable digital health interventions (DHI) provide an opportunity to monitor and support patients during their postoperative recovery. Lack of high-quality evidence is often cited as a barrier to DHI implementation. This review captures and appraises the current use, evidence base and reporting quality of mobile and wearable DHI following surgery. Keyword searches were performed within Embase, Cochrane Library, Web of Science and WHO Global Index Medicus databases, together with clinical trial registries and Google scholar. Studies involving patients undergoing any surgery requiring skin incision where postoperative outcomes were measured using a DHI following hospital discharge were included, with DHI defined as mobile and wireless technologies for health to improve health system efficiency and health outcomes. Methodological reporting quality was determined using the validated mobile health evidence reporting and assessment (mERA) guidelines. Bias was assessed using the Cochrane Collaboration tool for randomised studies or MINORS depending on study type. Overall, 6969 articles were screened, with 44 articles included. The majority (n = 34) described small prospective study designs, with a high risk of bias demonstrated. Reporting standards were suboptimal across all domains, particularly in relation to data security, prior patient engagement and cost analysis. Despite the potential of DHI to improve postoperative patient care, current progress is severely restricted by limitations in methodological reporting. There is an urgent need to improve reporting for DHI following surgery to identify patient benefit, promote reproducibility and encourage sustainability.

Early identification of patients at risk for delayed recovery of ambulation after elective abdominal surgery

BACKGROUND

Recovery of preoperative ambulation levels 1 month after surgery represents an important patient-centered outcome. The objective of this study is to identify clinical factors associated with the inability to regain baseline preoperative ambulation levels 28 days postoperatively.

METHODS

This is a prospective cohort study enrolling patients scheduled for elective inpatient abdominal operations. Daily ambulation (steps/day) was measured with a wristband accelerometer. Preoperative steps were recorded for at least 3 full calendar days before surgery. Postoperatively, daily steps were recorded for at least 28 days. The primary outcome was delayed recovery of ambulation, defined as inability to achieve 50% of preoperative baseline steps at 28 days postoperatively.

RESULTS

A total of 108 patients were included. Delayed recovery (< 50% of baseline preoperative steps/day) occurred in 32 (30%) patients. Clinical factors associated with delayed recovery after multivariable logistic regression included longer operative time (OR 1.37, 95% CI 1.05-1.79), open operative approach (OR 4.87, 95% CI 1.64-14.48) and percent recovery on POD3 (OR 0.73, 95% CI 0.56-0.96). In addition, patients with delayed ambulation recovery had increased rates of postoperative complications (16% vs 1%, p < 0.01) and readmission (28% vs 5%, p < 0.01).

CONCLUSION

After elective inpatient abdominal operations, nearly one in three patients do not recover 50% of their baseline preoperative steps 28 days postoperatively. Factors that can be used to identify these patients include longer operations, open operations and low ambulation levels on postoperative day #3. These data can be used to target rehabilitation efforts aimed at patients at greatest risk for poor ambulatory recovery.

Design and evaluation of the Afari: a three-wheeled mobility and balance support device for outdoor exercise

This article presents the engineering design and preliminary testing of the AfariTM mobility device and the integrated IntracTM activity tracking system. The patented Afari design is a three-wheeled device that assists users of any age with mobility impairments with outdoor exercise and movement in various environments and surfaces. We devised methods for testing of the Afari to ensure safe and flexible mobility assistance and demonstrated a high level of stability and structural integrity suitable for vigorous outdoor exercise. A smartphone-based sensing system, the Intrac, was designed for and integrated with the Afari to monitor the user's interaction forces and important gait parameters. The Intrac offers a graphical user interface for displaying and sharing measurements with users and providers, and the accuracy of its measurements was validated by testing its individual components. A preliminary subject study showed that the participants could use the Afari for various levels of weight compensation during walking, while the Intrac enabled the measurement of interactive forces on their arms and key gait parameters. The results demonstrate the potential of the Afari and Intrac to provide a safe walking experience in a variety of terrains and continuously monitor users' gait.

The Contribution of Machine Learning in the Validation of Commercial Wearable Sensors for Gait Monitoring in Patients: A Systematic Review

Gait, balance, and coordination are important in the development of chronic disease, but the ability to accurately assess these in the daily lives of patients may be limited by traditional biased assessment tools. Wearable sensors offer the possibility of minimizing the main limitations of traditional assessment tools by generating quantitative data on a regular basis, which can greatly improve the home monitoring of patients. However, these commercial sensors must be validated in this context with rigorous validation methods. This scoping review summarizes the state-of-the-art between 2010 and 2020 in terms of the use of commercial wearable devices for gait monitoring in patients. For this specific period, 10 databases were searched and 564 records were retrieved from the associated search. This scoping review included 70 studies investigating one or more wearable sensors used to automatically track patient gait in the field. The majority of studies (95%) utilized accelerometers either by itself (N = 17 of 70) or embedded into a device (N = 57 of 70) and/or gyroscopes (51%) to automatically monitor gait via wearable sensors. All of the studies (N = 70) used one or more validation methods in which “ground truth” data were reported. Regarding the validation of wearable sensors, studies using machine learning have become more numerous since 2010, at 17% of included studies. This scoping review highlights the current state of the ability of commercial sensors to enhance traditional methods of gait assessment by passively monitoring gait in daily life, over long periods of time, and with minimal user interaction. Considering our review of the last 10 years in this field, machine learning approaches are algorithms to be considered for the future. These are in fact data-based approaches which, as long as the data collected are numerous, annotated, and representative, allow for the training of an effective model. In this context, commercial wearable sensors allowing for increased data collection and good patient adherence through efforts of miniaturization, energy consumption, and comfort will contribute to its future success.

Impairment and Compensation in Dexterous Upper-Limb Function After Stroke. From the Direct Consequences of Pyramidal Tract Lesions to Behavioral Involvement of Both Upper-Limbs in Daily Activities

Impairments in dexterous upper limb function are a significant cause of disability following stroke. While the physiological basis of movement deficits consequent to a lesion in the pyramidal tract is well demonstrated, specific mechanisms contributing to optimal recovery are less apparent. Various upper limb interventions (motor learning methods, neurostimulation techniques, robotics, virtual reality, and serious games) are associated with improvements in motor performance, but many patients continue to experience significant limitations with object handling in everyday activities. Exactly how we go about consolidating adaptive motor behaviors through the rehabilitation process thus remains a considerable challenge. An important part of this problem is the ability to successfully distinguish the extent to which a given gesture is determined by the neuromotor impairment and that which is determined by a compensatory mechanism. This question is particularly complicated in tasks involving manual dexterity where prehensile movements are contingent upon the task (individual digit movement, grasping, and manipulation…) and its objective (placing, two step actions…), as well as personal factors (motivation, acquired skills, and life habits…) and contextual cues related to the environment (presence of tools or assistive devices…). Presently, there remains a lack of integrative studies which differentiate processes related to structural changes associated with the neurological lesion and those related to behavioral change in response to situational constraints. In this text, we shall question the link between impairments, motor strategies and individual performance in object handling tasks. This scoping review will be based on clinical studies, and discussed in relation to more general findings about hand and upper limb function (manipulation of objects, tool use in daily life activity). We shall discuss how further quantitative studies on human manipulation in ecological contexts may provide greater insight into compensatory motor behavior in patients with a neurological impairment of dexterous upper-limb function.

It's not about the capture, it's about what we can learn": a qualitative study of experts' opinions and experiences regarding the use of wearable sensors to measure gait and physical activity

BACKGROUND

The use of wearable sensor technology to collect patient health data, such as gait and physical activity, offers the potential to transform healthcare research. To maximise the use of wearable devices in practice, it is important that they are usable by, and offer value to, all stakeholders. Although previous research has explored participants' opinions of devices, to date, limited studies have explored the experiences and opinions of the researchers who use and implement them. Researchers offer a unique insight into wearable devices as they may have access to multiple devices and cohorts, and thus gain a thorough understanding as to how and where this area needs to progress. Therefore, the aim of this study was to explore the experiences and opinions of researchers from academic, industry and clinical contexts, in the use of wearable devices to measure gait and physical activity.

METHODS

Twenty professionals with experience using wearable devices in research were recruited from academic, industry and clinical backgrounds. Independent, semi-structured interviews were conducted, audio-recorded and transcribed. Transcribed texts were analysed using inductive thematic analysis.

RESULTS

Five themes were identified: (1) The positives and negatives of using wearable devices in research, (2) The routine implementation of wearable devices into research and clinical practice, (3) The importance of compromise in protocols, (4) Securing good quality data, and (5) A paradigm shift. Researchers overwhelmingly supported the use of wearable sensor technology due to the insights that they may provide. Though barriers remain, researchers were pragmatic towards these, believing that there is a paradigm shift happening in this area of research that ultimately requires mistakes and significant volumes of further research to allow it to progress.

CONCLUSIONS

Multiple barriers to the use of wearable devices in research and clinical practice remain, including data management and clear clinical utility. However, researchers strongly believe that the potential benefit of these devices to support and create new clinical insights for patient care, is greater than any current barrier. Multi-disciplinary research integrating the expertise of both academia, industry and clinicians is a fundamental necessity to further develop wearable devices and protocols that match the varied needs of all stakeholders.

Activity Tracking After Surgery: Does It Correlate With Postoperative Complications?

BACKGROUND

Postoperative ambulation is an important tenet in enhanced recovery programs. We quantitatively assessed the correlation of decreased postoperative ambulation with postoperative complications and delays in gastrointestinal function.

METHODS

Patients undergoing major abdominal surgery were fitted with digital ankle pedometers yielding continuous measurements of their ambulation. Primary endpoints were the overall and system-specific complication rates, with secondary endpoints being the time to first passage of flatus and stool, the length of hospital stay, and the rate of readmission.

RESULTS

100 patients were enrolled. We found a significant, independent inverse correlation between the number of steps on the first and second postoperative days (POD1/2) and the incidence of complications as well as the recovery of GI function and the likelihood of readmission (P < .05). POD2 step count was an independent risk factor for severe complications (P = .026).

DISCUSSION

Digitally quantified ambulation data may be a prognostic biomarker for the likelihood of severe postoperative complications.

Measuring Daily Compliance With Physical Activity Tracking in Ambulatory Surgery Patients: Comparative Analysis of Five Compliance Criteria

BACKGROUND

Physical activity trackers such as the Fitbit can allow clinicians to monitor the recovery of their patients following surgery. An important issue when analyzing activity tracker data is to determine patients' daily compliance with wearing their assigned device, using an appropriate criterion to determine a valid day of wear. However, it is currently unclear as to how different criteria can affect the reported compliance of patients recovering from ambulatory surgery. Investigating this issue can help to inform the use of activity data by revealing factors that may impact compliance calculations.

OBJECTIVE

This study aimed to understand how using different criteria can affect the reported compliance with activity tracking in ambulatory surgery patients. It also aimed to investigate factors that explain variation between the outcomes of different compliance criteria.

METHODS

A total of 62 patients who were scheduled to undergo total knee arthroplasty (TKA, ie, knee replacement) volunteered to wear a commercial Fitbit Zip activity tracker over an 8-week perioperative period. Patients were asked to wear the Fitbit Zip daily, beginning 2 weeks prior to their surgery and ending 6 weeks after surgery. Of the 62 patients who enrolled in the study, 20 provided Fitbit data and underwent successful surgery. The Fitbit data were analyzed using 5 different daily compliance criteria, which consider patients as compliant with daily tracking if they either register >0 steps in a day, register >500 steps in a day, register at least one step in 10 different hours of the day, register >0 steps in 3 distinct time windows, or register >0 steps in 3 out of 4 six-hour time windows. The criteria were compared in terms of compliance outcomes produced for each patient. Data were explored using heatmaps and line graphs. Linear mixed models were used to identify factors that lead to variation between compliance outcomes across the sample.

RESULTS

The 5 compliance criteria produce different outcomes when applied to the patients' data, with an average 24% difference in reported compliance between the most lenient and strictest criteria. However, the extent to which each patient's reported compliance was impacted by different criteria was not uniform. Some individuals were relatively unaffected, whereas others varied by up to 72%. Wearing the activity tracker as a clip-on device, rather than on the wrist, was associated with greater differences between compliance outcomes at the individual level (P=.004, r=.616). This effect was statistically significant (P<.001) in the first 2 weeks after surgery. There was also a small but significant main effect of age on compliance in the first 2 weeks after surgery (P=.040). Gender and BMI were not associated with differences in individual compliance outcomes. Finally, the analysis revealed that surgery has an impact on patients' compliance, with noticeable reductions in activity following surgery. These reductions affect compliance calculations by discarding greater amounts of data under strict criteria.

CONCLUSIONS

This study suggests that different compliance criteria cannot be used interchangeably to analyze activity data provided by TKA patients. Surgery leads to a temporary reduction in patients' mobility, which affects their reported compliance when strict thresholds are used. Reductions in mobility suggest that the use of lenient compliance criteria, such as >0 steps or windowed approaches, can avoid unnecessary data exclusion over the perioperative period. Encouraging patients to wear the device at their wrist may improve data quality by increasing the likelihood of patients wearing their tracker and ensuring that activity is registered in the 2 weeks after surgery.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03518866; https://clinicaltrials.gov/ct2/show/NCT03518866.

Wearable devices for patient monitoring in the early postoperative period: a literature review

The early postoperative period is a crucial stage in a patient's recovery as they are susceptible to a range of complications, with detection and management the key to avoiding long term consequences. Wearable devices are an innovative way of monitoring patient's post-intervention and may translate into improved patient outcomes, and reduced strain on healthcare resources, as they may facilitate safer and earlier discharge from the hospital setting. Several recent studies have investigated the use of wearable devices in postoperative monitoring. This review outlines the current literature including the range of wearable devices used for postoperative monitoring, the variety of surgeries investigated, and the outcomes assessed. A search of five electronic databases was performed. Data on the range of wearable devices, outcomes and surgeries investigated were extracted and synoptically analysed. Twenty-four articles were retrieved. Data on several different types of surgery were available and discussed. Most studies used wrist-mounted wearable devices and accelerometers or pedometers to assess physical activity metrics, including step counts and physical activity intensity (PAI), as markers of recovery. Wearable devices can provide objective data capture in the early postoperative phase to remotely monitor patients using various metrics including temperature, cardiac monitoring and physical activity. The majority of current research is focussed on wrist-mounted accelerometers and pedometers used to assess physical activity as a marker of postoperative function. Further research is required to demonstrate improved safety and cost-effectiveness of this technology.

Comparison of Wearable and Clinical Devices for Acquisition of Peripheral Nervous System Signals

A key access point to the functioning of the autonomic nervous system is the investigation of peripheral signals. Wearable devices (WDs) enable the acquisition and quantification of peripheral signals in a wide range of contexts, from personal uses to scientific research. WDs have lower costs and higher portability than medical-grade devices. However, the achievable data quality can be lower, and data are subject to artifacts due to body movements and data losses. It is therefore crucial to evaluate the reliability and validity of WDs before their use in research. In this study, we introduce a data analysis procedure for the assessment of WDs for multivariate physiological signals. The quality of cardiac and electrodermal activity signals is validated with a standard set of signal quality indicators. The pipeline is available as a collection of open source Python scripts based on the pyphysio package. We apply the indicators for the analysis of signal quality on data simultaneously recorded from a clinical-grade device and two WDs. The dataset provides signals of six different physiological measures collected from 18 subjects with WDs. This study indicates the need to validate the use of WDs in experimental settings for research and the importance of both technological and signal processing aspects to obtain reliable signals and reproducible results.

"It's Not as Simple as Just Looking at One Chart": A Qualitative Study Exploring Clinician's Opinions on Various Visualisation Strategies to Represent Longitudinal Actigraphy Data

Background

Data derived from wearable activity trackers may provide important clinical insights into disease progression and response to intervention, but only if clinicians can interpret it in a meaningful manner. Longitudinal activity data can be visually presented in multiple ways, but research has failed to explore how clinicians interact with and interpret these visualisations. In response, this study developed a variety of visualisations to understand whether alternative data presentation strategies can provide clinicians with meaningful insights into patient's physical activity patterns.

Objective

To explore clinicians' opinions on different visualisations of actigraphy data.

Methods

Four visualisations (stacked bar chart, clustered bar chart, linear heatmap and radial heatmap) were created using Matplotlib and Seaborn Python libraries. A focus group was conducted with 14 clinicians across 2 hospitals. Focus groups were audio-recorded, transcribed and analysed using inductive thematic analysis.

Results

Three major themes were identified: (1) the importance of context, (2) interpreting the visualisations and (3) applying visualisations to clinical practice. Although clinicians saw the potential value in the visualisations, they expressed a need for further contextual information to gain clinical benefits from them. Allied health professionals preferred more granular, temporal information compared to doctors. Specifically, physiotherapists favoured heatmaps, whereas the remaining members of the team favoured stacked bar charts. Overall, heatmaps were considered more difficult to interpret.

Conclusion

The current lack of contextual data provided by wearables hampers their use in clinical practice. Clinicians favour data presented in a familiar format and yet desire multi-faceted filtering. Future research should implement user-centred design processes to identify ways in which all clinical needs can be met, potentially using an interactive system that caters for multiple levels of granularity. Irrespective of how data is displayed, unless clinicians can apply it in a manner that best supports their role, the potential of this data cannot be fully realised.

Accelerometer-Based Human Activity Recognition for Patient Monitoring Using a Deep Neural Network

The objective of this study was to investigate the accuracy of a Deep Neural Network (DNN) in recognizing activities typical for hospitalized patients. A data collection study was conducted with 20 healthy volunteers (10 males and 10 females, age = 43 ± 13 years) in a simulated hospital environment. A single triaxial accelerometer mounted on the trunk was used to measure body movement and recognize six activity types: lying in bed, upright posture, walking, wheelchair transport, stair ascent and stair descent. A DNN consisting of a three-layer convolutional neural network followed by a long short-term memory layer was developed for this classification problem. Additionally, features were extracted from the accelerometer data to train a support vector machine (SVM) classifier for comparison. The DNN reached 94.52% overall accuracy on the holdout dataset compared to 83.35% of the SVM classifier. In conclusion, a DNN is capable of recognizing types of physical activity in simulated hospital conditions using data captured by a single tri-axial accelerometer. The method described may be used for continuous monitoring of patient activities during hospitalization to provide additional insights into the recovery process.

Embodiment of Wearable Technology: Qualitative Longitudinal Study

Background

Current technology innovations, such as wearables, have caused surprising reactions and feelings of deep connection to devices. Some researchers are calling mobile and wearable technologies cognitive prostheses, which are intrinsically connected to individuals as if they are part of the body, similar to a physical prosthesis. Additionally, while several studies have been performed on the phenomenology of receiving and wearing a physical prosthesis, it is unknown whether similar subjective experiences arise with technology.

Objective

In one of the first qualitative studies to track wearables in a longitudinal investigation, we explore whether a wearable can be embodied similar to a physical prosthesis. We hoped to gain insights and compare the phases of embodiment (ie, initial adjustment to the prosthesis) and the psychological responses (ie, accept the prosthesis as part of their body) between wearables and limb prostheses. This approach allowed us to find out whether this pattern was part of a cyclical (ie, period of different usage intensity) or asymptotic (ie, abandonment of the technology) pattern.

Methods

We adapted a limb prosthesis methodological framework to be applied to wearables and conducted semistructured interviews over a span of several months to assess if, how, and to what extent individuals come to embody wearables similar to prosthetic devices. Twelve individuals wore fitness trackers for 9 months, during which time interviews were conducted in the following three phases: after 3 months, after 6 months, and at the end of the study after 9 months. A deductive thematic analysis based on Murray’s work was combined with an inductive approach in which new themes were discovered.

Results

Overall, the individuals experienced technology embodiment similar to limb embodiment in terms of adjustment, wearability, awareness, and body extension. Furthermore, we discovered two additional themes of engagement/reengagement and comparison to another device or person. Interestingly, many participants experienced a rarely reported phenomenon in longitudinal studies where the feedback from the device was counterintuitive to their own beliefs. This created a blurring of self-perception and a dilemma of “whom” to believe, the machine or one’s self.

Conclusions

There are many similarities between the embodiment of a limb prosthesis and a wearable. The large overlap between limb and wearable embodiment would suggest that insights from physical prostheses can be applied to wearables and vice versa. This is especially interesting as we are seeing the traditionally “dumb” body prosthesis becoming smarter and thus a natural merging of technology and body. Future longitudinal studies could focus on the dilemma people might experience of whether to believe the information of the device over their own thoughts and feelings. These studies might take into account constructs, such as technology reliance, autonomy, and levels of self-awareness.

Implementation of Wearable Sensing Technology for Movement: Pushing Forward into the Routine Physical Rehabilitation Care Field

While the promise of wearable sensor technology to transform physical rehabilitation has been around for a number of years, the reality is that wearable sensor technology for the measurement of human movement has remained largely confined to rehabilitation research labs with limited ventures into clinical practice. The purposes of this paper are to: (1) discuss the major barriers in clinical practice and available wearable sensing technology; (2) propose benchmarks for wearable device systems that would make it feasible to implement them in clinical practice across the world and (3) evaluate a current wearable device system against the benchmarks as an example. If we can overcome the barriers and achieve the benchmarks collectively, the field of rehabilitation will move forward towards better movement interventions that produce improved function not just in the clinic or lab, but out in peoples' homes and communities.

Postoperative delirium is associated with decreased recovery of ambulation one-month after surgery

BACKGROUND

We hypothesized that postoperative delirium is associated with diminished recovery toward baseline preoperative ambulation levels one-month postoperatively.

METHODS

Patients included were ≥60 years old undergoing inpatient operations. Ambulation was measured as steps/day using an accelerometer worn for ≥3-days preoperatively and ≥28-days postoperatively. Primary outcome was the percent recovery of preoperative steps.

RESULTS

109 patients were included; 17 (16%) developed postoperative delirium. Recovery of ambulation toward preoperative baseline at postoperative day-28 was decreased in delirium group (34% vs. 69%; p < 0.01). Immediate postoperative ambulation was similar in the delirium vs. no-delirium groups (p = 0.79). Delirium occurred on average on postoperative 3 ± 4 days. Subsequently, ambulation was decreased in the delirium group compared to non-delirium group at postoperative week-1 (p = 0.01), week-2 (p = 0.02), week-3 (p < 0.01) and week-4 (p < 0.01).

CONCLUSION

Patients undergoing inpatient operations who develop delirium recover only one-third of their baseline steps one-month postoperatively. Postoperative delirium results in a decreased recovery towards baseline ambulation for at least 4-weeks following major operations in comparison to non-delirious patients. The decrease in ambulation in the delirium versus no-delirium groups occurred after the occurrence of postoperative delirium.

Use of Fitbit Technology Does Not Impact Health Biometrics in a Community of Older Adults

Introduction: To evaluate if the offering of Fitbit technology led to changes in cardiovascular health metrics in a cohort of older adults. Methods: A retrospective cohort study was developed in two community-embedded health monitoring sites, located in aggregate housing communities for older adults in Westchester County, NY. Participants included older adults (55 years or older) enrolled in the Telehealth Intervention Programs for Seniors (TIPS) initiative, a community-embedded remote patient monitoring initiative. Weekly blood pressure, heart rate, weight, and blood oxygenation were taken on all participants. For participants who accepted a Fitbit Zip device, a weekly step count was also collected. Results: Ninety-four TIPS participants were offered Fitbit technology. Thirty participants accepted the technology and used it for a minimum of 6 months. No significant differences in any of the regularly acquired biometrics were noted between Fitbit users and non-Fitbit users. Across all participants, regardless of Fitbit use, there was a significant decrease in systolic blood pressure (SBP) over time. Conclusions: Neither Fitbit Zip ownership or compliance to Fitbit Zip usage influenced any of the biometrics taken as part of the TIPS. However, participation in the TIPS initiative may have an overall positive effect on SBP in older adults.

Improving mobile health apps usage: a quantitative study on mPower data of Parkinson's disease

Purpose

The emergence of mobile health (mHealth) products has created a capability of monitoring and managing the health of patients with chronic diseases. These mHealth technologies would not be beneficial unless they are adopted and used by their target users. This study identifies key factors affecting the usage of mHealth apps based on user usage data collected from an mHealth app.

Design/methodology/approach

Using a dataset collected from an mHealth app named mPower, developed for patients with Parkinson's disease (PD), this paper investigated the effects of disease diagnosis, disease progression and mHealth app difficulty level on app usage, while controlling for user information. App usage is measured by five different activity counts of the app.

Findings

The results across five measures of mHealth app usage vary slightly. On average, previous professional diagnosis and high user performance scores encourage user participation and engagement, while disease progression hinders app usage.

Research limitations/implications

The findings potentially provide insights into better design and promotion of mHealth products and improve the capability of health management of patients with chronic diseases.

Originality/value

Studies on the mHealth app usage are critical but sparse because large-scale and reliable mHealth app usage data are limited. Unlike earlier works based solely on survey data, this research used a large user usage data collected from an mHealth app to study key factors affecting app usage. The methods presented in this study can serve as a pioneering work for the design and promotion of mHealth technologies.

Is Activity Tracker-Measured Ambulation an Accurate and Reliable Determinant of Postoperative Quality of Recovery? A Prospective Cohort Validation Study

BACKGROUND

Quality of recovery (QOR) instruments measure patients' ability to return to baseline health status after surgery. Whether, and the extent to which, postoperative ambulation contributes to QOR is unclear, in part due to the lack of valid tools to measure ambulation in clinical settings. This cohort study of the cesarean delivery surgical model examines the accuracy and reliability of activity trackers in quantifying early postoperative ambulation and investigates the correlation between ambulation and QOR.

METHODS

A prospective cohort of 200 parturients undergoing cesarean delivery between July 2015 and June 2017 was fitted with wrist-worn activity trackers immediately postpartum. The trackers were collected 24 hours later, along with QOR assessments (QoR-15 scale). The relationship between QOR and various covariates, including ambulation, was explored using multivariable linear regression and Spearman correlation (ρ). Forty-eight parturients fitted with 2 trackers also completed a walk exercise accompanied by a step-counting assessor, to evaluate accuracy, inter-, and intradevice reliability using interclass correlation (ICC).

RESULTS

Compared to step counting, activity trackers had high accuracy (ICC = 0.93) and excellent inter- and intradevice reliability (ICC = 0.98 and 0.96, respectively). Correlation analysis suggested that early ambulation is moderately correlated with postcesarean QoR-15 scores, with a ρ (95% confidence interval) equivalent to 0.56 (0.328-0.728). Regression analysis suggested that ambulation is a determinant of postcesarean QoR-15 scores, with an effect estimate (95% confidence interval) equivalent to 0.002 (0.001-0.003). Ambulation was also associated with all QoR-15 domains, except psychological support. The patient's acceptable symptom state (subjective threshold for good ambulation) in the first 24 hours was 287 steps.

CONCLUSIONS

This study demonstrated the accuracy and reliability of activity trackers in measuring ambulation in clinical settings and suggested that postoperative ambulation is a determinant of postoperative QOR. A hypothetical implication of our findings is that interventions that improve ambulation may also help to enhance QOR, but further research is needed to establish a causal relationship.

Changing the Physical Activity Behavior of Adults With Fitness Trackers: A Systematic Review and Meta-Analysis

OBJECTIVE

To examine whether a fitness tracker (FT) intervention changes physical activity (PA) behavior compared to a control condition or compared to an alternative intervention.

DATA SOURCE

Searches between January 01, 2010, and January 01, 2019, were conducted in PubMed, CINAHL, Cochrane CENTRAL, EMBASE, and PsycINFO.

INCLUSION/EXCLUSION CRITERIA

Randomized clinical trials of adults using an FT to change PA behavior were included. Nonclinical trials, studies that included the delivery of structured exercise, and/or studies that only used the FT to assess PA were excluded.

DATA EXTRACTION

Extracted features included characteristics of the study population, intervention components, PA outcomes, and results.

DATA SYNTHESIS

Papers were pooled in a statistical meta-analysis using a fixed effects model. Where statistical pooling was not possible, standardized mean difference (SMD) and 95% confidence intervals (CI) were calculated. Findings were presented in a narrative form and tables.

RESULTS

Of 2076 articles found, 21 were included in the review. A small yet significant positive effect (SMD = 0.25, 95% CI = 0.17-0.32; P < .01; I² = 56.9%; P = .03) was found in step count for interventions compared to control. A small yet significant negative effect (SMD = -0.11, 95% CI = -0.20 to -0.02; P = .02; I² = 58.2%; P = 0.03) was found in moderate-to-vigorous PA for interventions compared to an alternative intervention.

CONCLUSION

Trackers may enhance PA interventions, as a general positive effect is found in step count compared to a control. However, there is no evidence of a positive effect when interventions are compared to an alternative intervention. It is unknown whether results are due to other intervention components and/or clinical heterogeneity.

Is Wearable Technology Becoming Part of Us? Developing and Validating a Measurement Scale for Wearable Technology Embodiment

BACKGROUND

To experience external objects in such a way that they are perceived as an integral part of one's own body is called embodiment. Wearable technology is a category of objects, which, due to its intrinsic properties (eg, close to the body, inviting frequent interaction, and access to personal information), is likely to be embodied. This phenomenon, which is referred to in this paper as wearable technology embodiment, has led to extensive conceptual considerations in various research fields. These considerations and further possibilities with regard to quantifying wearable technology embodiment are of particular value to the mobile health (mHealth) field. For example, the ability to predict the effectiveness of mHealth interventions and knowing the extent to which people embody the technology might be crucial for improving mHealth adherence. To facilitate examining wearable technology embodiment, we developed a measurement scale for this construct.

OBJECTIVE

This study aimed to conceptualize wearable technology embodiment, create an instrument to measure it, and test the predictive validity of the scale using well-known constructs related to technology adoption. The introduced instrument has 3 dimensions and includes 9 measurement items. The items are distributed evenly between the 3 dimensions, which include body extension, cognitive extension, and self-extension.

METHODS

Data were collected through a vignette-based survey (n=182). Each respondent was given 3 different vignettes, describing a hypothetical situation using a different type of wearable technology (a smart phone, a smart wristband, or a smart watch) with the purpose of tracking daily activities. Scale dimensions and item reliability were tested for their validity and Goodness of Fit Index (GFI).

RESULTS

Convergent validity of the 3 dimensions and their reliability were established as confirmatory factor analysis factor loadings (>0.70), average variance extracted values (>0.50), and minimum item to total correlations (>0.40) exceeded established threshold values. The reliability of the dimensions was also confirmed as Cronbach alpha and composite reliability exceeded 0.70. GFI testing confirmed that the 3 dimensions function as intercorrelated first-order factors. Predictive validity testing showed that these dimensions significantly add to multiple constructs associated with predicting the adoption of new technologies (ie, trust, perceived usefulness, involvement, attitude, and continuous intention).

CONCLUSIONS

The wearable technology embodiment measurement instrument has shown promise as a tool to measure the extension of an individual's body, cognition, and self, as well as predict certain aspects of technology adoption. This 3-dimensional instrument can be applied to mixed method research and used by wearable technology developers to improve future versions through such things as fit, improved accuracy of biofeedback data, and customizable features or fashion to connect to the users' personal identity. Further research is recommended to apply this measurement instrument to multiple scenarios and technologies, and more diverse user groups.

Examining adherence to activity monitoring devices to improve physical activity in adults with cardiovascular disease: A systematic review

BACKGROUND

Activity monitoring devices are currently being used to facilitate and monitor physical activity. No prior review has examined adherence to the use of activity monitoring devices amongst adults with cardiovascular disease.

METHODS

Literature from June 2012 to October 2017 was evaluated to examine the extent of adherence to any activity monitoring device used to collect objective physical activity data. Randomized control trials comparing usual care against the use of an activity monitoring device, in a community intervention for adults from any cardiovascular diagnostic group, were included. A systematic search of databases and clinical trials registers was conducted using Joanna Briggs Institute methodology.

RESULTS

Of 10 eligible studies, two studies reported pedometer use and eight accelerometer use. Six studies addressed the primary outcome. Mean adherence was 59.1% (range 39.6% to 85.7%) at last follow-up. Studies lacked equal representation by gender (28.6% female) and age (range 42 to 82 years).

CONCLUSION

This review indicates that current research on activity monitoring devices may be overstated due to the variability in adherence. Results showed that physical activity tracking in women and in young adults have been understudied.

Physical activity monitors can be successfully implemented to assess perioperative activity in urologic surgery

BACKGROUND

Mobile health and physical activity monitors (PAMs) are emerging technologies allowing patients to track multiple health parameters. These parameters could be useful in monitoring and modifying the perioperative health of urology patients. We performed a pilot study and describe a model for which to implement mHealth applications in a urology population.

METHODS

Patients undergoing robotic assisted retropubic prostatectomy were screened for inclusion and provided with Fitbit® Charge HRTM (Boston, MA, USA) devices. Patients were fitted with the device during the preoperative visit and instructed to wear before and after surgery. Biophysical data was collected and patient acceptance was assessed with a Mobile Physical Activity Monitor Questionnaire (MPAMQ).

RESULTS

Forty-six patients met inclusion criteria. Median duration of PAM usage was one and seven days preoperatively and postoperatively. Postoperatively, there was a reduction in median daily steps compared to preoperatively (2,782 vs. 3,907, P=0.024), but no statistically significant difference in minutes slept or nighttime awakenings. Obese (BMI ≥30) and older men (≥65 years) had a greater reduction in steps after surgery (P<0.001 and P=0.055), whereas there was no difference in non-obese and men age <65. Patients with BMI ≥30 took 35% fewer steps postoperatively than BMI <30 (P=0.017). The majority of patients (82%) reported a medical benefit and 95% were satisfied with using PAM technology in the perioperative period.

CONCLUSIONS

PAM effectively captures perioperative biophysical parameters and is associated with high patient satisfaction. Clinically, obese and elderly men appear to have significantly reduced activity following prostatectomy.

Physiotherapists' and Physiotherapy Students' Perspectives on the Use of Mobile or Wearable Technology in Their Practice

Purpose: Although extensive research has been carried out on the determinants of mobile or wearable health care technology (mHealth), as well as on its acceptance by patients and other health care providers, very little research has been done on physiotherapists' perspectives on the use of mHealth in their current or future practice. The aims of this study were to (1) explore the attitudes of physiotherapists toward mHealth using a modified technology acceptance model questionnaire, (2) understand the applications and delivery paradigms that are most desirable, and (3) assess the content validity of the questionnaire. Method: The questionnaire was administered online. Participants (n=76) were recruited using snowball and convenience sampling. Data were analyzed using factor analysis and partial least-squares path modelling. Results: Results indicate that perceived usefulness and perceived ease of use were related to early adoptive behaviour among participants. We found no evidence that age, gender, experience, or practice setting influenced early adoptive behaviour. Participants demonstrated favourable attitudes toward mHealth tools in clinical practice. Conclusions: This article provides initial insights into factors that are likely to be significant determinants of adoption of mHealth among physiotherapists. Further work, including qualitative research, will help to identify personal and institutional factors that will improve the acceptance of mHealth.

Accuracy of a Wrist-Worn Heart Rate Sensing Device during Elective Pediatric Surgical Procedures

The reliability of wearable photoplethysmography (PPG) sensors to measure heart rate (HR) in hospitalized patients has only been demonstrated in adults. We evaluated the accuracy of HR monitoring with a personal fitness tracker (PFT) in children undergoing surgery. HR monitoring was performed using a wrist-worn PFT (Fitbit Charge HR) in 30 children (8.21 ± 3.09 years) undergoing laparoscopy (n = 8) or open surgery (n = 22). HR values were analyzed preoperatively and during surgery. The accuracy of HR recordings was compared with measurements recorded during continuous electrocardiographic (cECG) monitoring; HRs derived from continuous monitoring with pulse oximetry (SpO2R) were used as a positive control. PFT-derived HR values were in agreement with those recorded during cECG (r = 0.99) and SpO2R (r = 0.99) monitoring. PFT performance remained high in children < 8 years (r = 0.99), with a weight < 30 kg (r = 0.99) and when the HR was < 70 beats per minute (bpm) (r = 0.91) or > 140 bpm (r = 0.99). PFT accuracy was similar during laparoscopy and open surgery, as well as preoperatively and during the intervention (r > 0.9). PFT–derived HR showed excellent accuracy compared with HRs measured by cECG and SpO2R during pediatric surgical procedures. Further clinical evaluation is needed to define whether PFTs can be used in different health care settings.

Using Activity Trackers to Quantify Postpartum Ambulation

Background

Early postoperative ambulation is associated with enhanced functional recovery, particularly in the postpartum population, but ambulation questionnaires are limited by recall bias. This observational study aims to objectively quantify ambulation after neuraxial anesthesia and analgesia for cesarean delivery and vaginal delivery, respectively, by using activity tracker technology. The hypothesis was that vaginal delivery is associated with greater ambulation during the first 24 h postdelivery, compared to cesarean delivery.

Methods

Parturients having first/second cesarean delivery under spinal anesthesia or first/second vaginal delivery under epidural analgesia between July 2015 and December 2016 were recruited. Patients with significant comorbidities or postpartum complications were excluded, and participants received standard multimodal analgesia. Mothers were fitted with wrist-worn activity trackers immediately postdelivery, and the trackers were recollected 24 h later. Rest and dynamic postpartum pain scores at 2, 6, 12, 18, and 24 h and quality of recovery (QoR-15) at 12 and 24 h were assessed.

Results

The study analyzed 173 patients (cesarean delivery: 76; vaginal delivery: 97). Vaginal delivery was associated with greater postpartum ambulation (44%) compared to cesarean delivery, with means ± SD of 1,205 ± 422 and 835 ± 381 steps, respectively, and mean difference (95% CI) of 370 steps (250, 490; P &lt; 0.0001). Although both groups had similar pain scores and opioid consumption (less than 1.0 mg of morphine), vaginal delivery was associated with superior QoR-15 scores, with 9.2 (0.6, 17.8; P = 0.02) and 8.2 (0.1, 16.3; P = 0.045) differences at 12 and 24 h, respectively.

Conclusions

This study objectively demonstrates that vaginal delivery is associated with greater early ambulation and functional recovery compared to cesarean delivery. It also establishes the feasibility of using activity trackers to evaluate early postoperative ambulation after neuraxial anesthesia and analgesia.

Consumer physical activity tracking device ownership and use among a population-based sample of adults

Consumer physical activity tracking devices (PATs) have gained popularity to support individuals to be more active and less sedentary throughout the day. Wearable PATs provide real-time feedback of various fitness-related metrics such as tracking steps, sedentary time, and distance walked. The purpose of this study was to examine the prevalence and correlates of PAT ownership and use among a population-based sample of adults. A representative sample of adults ≥18 years (N = 1,215) from Alberta, Canada were recruited through random-digit dialing and responded to a questionnaire via computer-assisted telephone interviewing methods in summer 2016. Questionnaires assessed demographic and health behaviour variables, and items were designed to assess PAT ownership and usage. Logistic regression analysis (odds ratios) was used to assess correlates of PAT ownership and use. On average, participants (N = 1,215) were 53.9 (SD 16.7) years and 50.1% were female. Of the sample, 19.6% (n = 238) indicated they currently own and use a PAT. Participants who owned a PAT wore their device on average 23.2 days within the past month. Currently owning a PAT was significantly associated with being female (OR = 1.41, CI: 1.10 to 1.82), being <60 years of age (OR = 1.86, CI: 1.37 to 2.53), having at least some post secondary education (OR = 1.88, CI: 1.36 to 2.60), having a BMI ≥25 (OR = 1.52, CI: 1.16 to 1.99), and meeting physical activity guidelines (OR = 1.45, CI: 1.12 to 1.88). Similar correlates emerged for PAT use. Correlates significantly associated with PAT use and ownership included being female, being less than 60 years of age, having a post-secondary education, meeting physical activity guidelines, and being overweight/obese. This is the first study to examine characteristics of PAT ownership and use among Canadian adults.

Using patient data to optimize an expert-based guideline on convalescence recommendations after gynecological surgery: a prospective cohort study

BACKGROUND

Convalescence advice is often based on tradition and anecdote from health care providers, rather than being based on experiences from patients themselves. The aim of this study was to analyse recovery in terms of resumption of various daily activities including work, following different laparoscopic and abdominal surgery in order to optimize an expert-based guideline on convalescence recommendations.

METHODS

This is a prospective cohort study conducted in nine general and one university hospital in the Netherlands. Women aged 18-65 years and scheduled for a hysterectomy (laparoscopic, vaginal, abdominal) and/or laparoscopic adnexal surgery (n = 304) were eligible to participate. Preoperatively, participants were provided with tailored expert-based convalescence recommendations on the graded resumption of several daily activities including sitting, standing, walking, climbing stairs, bending, lifting, driving, cycling, household chores, sport activities and return to work (RTW). Postoperatively, time until the resumption of these activities was tracked. Convalescence recommendations were considered correct when at least 25% and less than 50% of the women were able to resume an activity before or at the recommended recovery time.

RESULTS

There was a wide variation in the duration until the resumption of daily activities within and between groups of patients undergoing different types of surgery. Recovery times lengthened with increasing levels of physical burden as well as with increasing levels of invasiveness of the surgery. For the majority of activities actual recovery times exceeded the recovery time recommended by the expert panel.

CONCLUSIONS

This study provided insight in the resumption of daily activities after gynecological surgery and the adequacy of an expert-based convalescence guideline in clinical practice. Patient data was used to optimize the convalescence recommendations.

TRIAL REGISTRATION

Dutch trial registry, NTR2087 (August 2009) and NTR2933 (June 2011).

Promise of Wearable Physical Activity Monitors in Oncology Practice

Commercially available physical activity monitors provide clinicians an opportunity to obtain oncology patient health measures to an unprecedented degree. These devices can provide objective and quantifiable measures of physical activity, which are not subject to errors or bias of self-reporting or shorter duration of formal testing. Prior work on so-called quantified-self data was based on older-generation, research-grade accelerometers, which laid the foundation for consumer-based physical activity monitoring devices to be validated as a feasible and reliable tool in patients with cancer. Physical activity monitors are being used in chronic conditions including chronic obstructive pulmonary disease, congestive heart failure, diabetes mellitus, and obesity. Differing demographics, compounded with higher symptom and treatment burdens in patients with cancer, imply that additional work is needed to understand the unique strengths and weaknesses of physical activity monitors in this population. Oncology programs can systematically implement these tools into their workflows in an adaptable and iterative manner. Translating large amounts of data collected from an individual physical activity monitoring device into clinically relevant information requires sophisticated data compilation and reduction. In this article, we summarize the characteristics of older- and newer-generation physical activity monitors, review the validation of physical activity monitors with respect to health-related quality-of-life assessments, and describe the current role of these devices for the practicing oncologist. We also highlight the challenges and next steps needed for physical activity monitors to provide relevant information that can change the current state of oncology practice.

Early warnings of heart rate deterioration

Hospitals can experience difficulty in detecting and responding to early signs of patient deterioration leading to late intensive care referrals, excess mortality and morbidity, and increased hospital costs. Our study aims to explore potential indicators of physiological deterioration by the analysis of vital-signs. The dataset used comprises heart rate (HR) measurements from MIMIC II waveform database, taken from six patients admitted to the Intensive Care Unit (ICU) and diagnosed with severe sepsis. Different indicators were considered: 1) generic early warning indicators used in ecosystems analysis (autocorrelation at-1-lag (ACF1), standard deviation (SD), skewness, kurtosis and heteroskedasticity) and 2) entropy analysis (kernel entropy and multi scale entropy). Our preliminary findings suggest that when a critical transition is approaching, the equilibrium state changes what is visible in the ACF1 and SD values, but also by the analysis of the entropy. Entropy allows to characterize the complexity of the time series during the hospital stay and can be used as an indicator of regime shifts in a patient's condition. One of the main problems is its dependency of the scale used. Our results demonstrate that different entropy scales should be used depending of the level of entropy verified.

Translational bioinformatics in the era of real-time biomedical, health care and wellness data streams

Monitoring and modeling biomedical, health care and wellness data from individuals and converging data on a population scale have tremendous potential to improve understanding of the transition to the healthy state of human physiology to disease setting. Wellness monitoring devices and companion software applications capable of generating alerts and sharing data with health care providers or social networks are now available. The accessibility and clinical utility of such data for disease or wellness research are currently limited. Designing methods for streaming data capture, real-time data aggregation, machine learning, predictive analytics and visualization solutions to integrate wellness or health monitoring data elements with the electronic medical records (EMRs) maintained by health care providers permits better utilization. Integration of population-scale biomedical, health care and wellness data would help to stratify patients for active health management and to understand clinically asymptomatic patients and underlying illness trajectories. In this article, we discuss various health-monitoring devices, their ability to capture the unique state of health represented in a patient and their application in individualized diagnostics, prognosis, clinical or wellness intervention. We also discuss examples of translational bioinformatics approaches to integrating patient-generated data with existing EMRs, personal health records, patient portals and clinical data repositories. Briefly, translational bioinformatics methods, tools and resources are at the center of these advances in implementing real-time biomedical and health care analytics in the clinical setting. Furthermore, these advances are poised to play a significant role in clinical decision-making and implementation of data-driven medicine and wellness care.

Do activity monitors increase physical activity in adults with overweight or obesity? A systematic review and meta-analysis

OBJECTIVE

To systematically assess contemporary knowledge regarding behavioral physical activity interventions including an activity monitor (BPAI+) in adults with overweight or obesity.

METHODS

PubMed/MEDLINE, Embase, CINAHL, PsycINFO, CENTRAL, and PEDro were searched for eligible full-text articles up to 1 July 2015. Studies eligible for inclusion were (randomized) controlled trials describing physical activity outcomes in adults with overweight or obesity. Methodological quality was independently assessed employing the Cochrane Collaboration's tool for risk of bias.

RESULTS

Fourteen studies (1,157 participants) were included for systematic review and 11 for meta-analysis. A positive trend in BPAI+ effects on several measures of physical activity was ascertained compared with both wait list or usual care and behavioral physical activity interventions without an activity monitor (BPAI-). No convincing evidence of BPAI+ effectiveness on weight loss was found compared with BPAI-.

CONCLUSIONS

Behavioral physical activity interventions with an activity monitor increase physical activity in adults with overweight or obesity. Also, adding an activity monitor to behavioral physical activity interventions appears to increase the effect on physical activity, although current evidence has not yet provided conclusive evidence for its effectiveness.

Comparison of Consumer and Research Monitors under Semistructured Settings

PURPOSE

This study evaluated the relative validity of different consumer and research activity monitors during semistructured periods of sedentary activity, aerobic exercise, and resistance exercise.

METHODS

Fifty-two (28 male and 24 female) participants age 18-65 yr performed 20 min of self-selected sedentary activity, 25 min of aerobic exercise, and 25 min of resistance exercise, with 5 min of rest between each activity. Each participant wore five wrist-worn consumer monitors [Fitbit Flex, Jawbone Up24, Misfit Shine (MS), Nike+ Fuelband SE (NFS), and Polar Loop] and two research monitors [ActiGraph GT3X+ on the waist and BodyMedia Core (BMC) on the arm] while being concurrently monitored with Oxycon Mobile (OM), a portable metabolic measuring system. Energy expenditure (EE) on different activity sessions was measured by OM and estimated by all monitors.

RESULTS

Mean absolute percent error (MAPE) values for the full 80-min protocol ranged from 15.3% (BMC) to 30.4% (MS). EE estimates from ActiGraph GT3X+ were found to be equivalent to those from OM (± 10% equivalence zone, 285.1-348.5). Correlations between OM and the various monitors were generally high (ranged between 0.71 and 0.90). Three monitors had MAPE values lower than 20% for sedentary activity: BMC (15.7%), MS (18.2%), and NFS (20.0%). Two monitors had MAPE values lower than 20% for aerobic exercise: BMC (17.2%) and NFS (18.5%). None of the monitors had MAPE values lower than 25% for resistance exercise.

CONCLUSION

Overall, the research monitors and Fitbit Flex, Jawbone Up24, and NFS provided reasonably accurate total EE estimates at the individual level. However, larger error was evident for individual activities, especially resistance exercise. Further research is needed to examine these monitors across various activities and intensities as well as under real-world conditions.

Physical Activity Measured with Accelerometer and Self-Rated Disability in Lumbar Spine Surgery: A Prospective Study

STUDY DESIGN

Prospective observational study.

OBJECTIVE

Patient-based subjective ratings of symptoms and function have traditionally been used to gauge the success and extent of recovery following spine surgery. The main drawback of this type of assessment is the inherent subjectivity involved in patient scoring. We aimed to objectively measure functional outcome in patients having lumbar spine surgery using quantitative physical activity measurements derived from accelerometers.

METHODS

A prospective study of 30 patients undergoing spine surgery was conducted with subjective outcome scores (visual analog scale [VAS], Oswestry Disability Index [ODI] and Short Form 12 [SF-12]) recorded; patients were given a Fitbit accelerometer (Fitbit Inc., San Francisco, California, United States) at least 7 days in advance of surgery to record physical activity (step count, distance traveled, calories burned) per day. Following surgery, postoperative activity levels were reported at 1-, 2-, and 3-month follow-up.

RESULTS

Of the 28 compliant patients who completed the full trial period, mean steps taken per day increased 58.2% (p = 0.008) and mean distance traveled per day increased 63% (p = 0.0004) at 3-month follow-up. Significant improvements were noted for mean changes in VAS back pain, VAS leg pain, ODI, and SF-12 Physical Component Summary (PCS) scores. There was no significant correlation between the improvement in steps or distance traveled per day with improvements in VAS back or leg pain, ODI, or PCS scores at follow-up.

CONCLUSIONS

High compliance and statistically significant improvement in physical activity were demonstrated in patients who had lumbar decompression and lumbar fusion. There was no significant correlation between improvements in subjective clinical outcome scores with changes in physical activity measurements at follow-up. Limitations of the present study include its small sample size, and the validity of objective physical activity measurements should be assessed in future larger, prospective studies.

Reciprocal Reinforcement Between Wearable Activity Trackers and Social Network Services in Influencing Physical Activity Behaviors

BACKGROUND

Wearable activity trackers (WATs) are emerging consumer electronic devices designed to support physical activities (PAs), which are based on successful behavior change techniques focusing on goal-setting and frequent behavioral feedbacks. Despite their utility, data from both recent academic and market research have indicated high attrition rates of WAT users. Concurrently, evidence shows that social support (SS), delivered/obtained via social network services or sites (SNS), could increase adherence and engagement of PA intervention programs. To date, relatively few studies have looked at how WATs and SS may interact and affect PAs.

OBJECTIVE

The purpose of this study was to explore how these two Internet and mobile technologies, WATs and SNS, could work together to foster sustainable PA behavior changes and habits among middle-aged adults (40-60 years old) in Taiwan.

METHODS

We used purposive sampling of Executive MBA Students from National Taiwan University of Science and Technology to participate in our qualitative research. In-depth interviews and focus groups were conducted with a total of 15 participants, including 9 WAT users and 6 nonusers. Analysis of the collected materials was done inductively using the thematic approach with no preset categories. Two authors from different professional backgrounds independently annotated and coded the transcripts, and then discussed and debated until consensus was reached on the final themes.

RESULTS

The thematic analysis revealed six themes: (1) WATs provided more awareness than motivation in PA with goal-setting and progress monitoring, (2) SS, delivered/obtained via SNS, increased users' adherence and engagement with WATs and vice versa, (3) a broad spectrum of configurations would be needed to deliver WATs with appropriately integrated SS functions, (4) WAT design, style, and appearance mattered even more than those of smartphones, as they are body-worn devices, (5) the user interfaces of WATs left a great deal to be desired, and (6) privacy concerns must be addressed before more mainstream consumers would consider adopting WATs.

CONCLUSIONS

Participants perceived WATs as an awareness tool to understand one's PA level. It is evident from our study that SS, derived from SNS and other pertinent vehicles such as the LINE social messaging application (similar to WhatsApp and WeChat), will increase the engagement and adherence of WAT usage. Combining WATs and SNS enables cost-effective, scalable PA intervention programs with end-to-end services and data analytics capabilities, to elevate WATs from one-size-fits-all consumer electronics to personalized PA assistants.

A cloud-based mobile system to improve respiratory therapy services at home

Chronic respiratory diseases are one of the most prevalent health problems in the world. Treatment for these kind of afflictions often take place at home, where the continuous care of a medical specialist is frequently beyond the economical means of the patient, therefore having to rely on informal caregivers (family, friends, etc.). Unfortunately, these treatments require a deep involvement on their part, which results in a heavy burden on the caregivers' routine and usually end up deteriorating their quality of life. In recent years, mHealth and eHealth applications have gained a wide interest in academia due to new capabilities enabled by the latest advancements in mobile technologies and wireless communication infrastructure. These innovations have resulted in several applications that have successfully managed to improve automatic patient monitoring and treatment and to bridge the distance between patients, caregivers and medical specialists. We therefore seek to move this trend forward by now pushing these capabilities into the field of respiratory therapies in order to assist patients with chronic respiratory diseases with their treatment, and to improve both their own and their caregivers' quality of life. This paper presents a cloud-based mobile system to support and improve homecare for respiratory diseases. The platform described uses vital signs monitoring as a way of sharing data between hospitals, caregivers and patients. Using an iterative research approach and the user's direct feedback, we show how mobile technologies can improve a respiratory therapy and a family's quality of life.