Monitoring postures and motions of hospitalized patients using sensor technology: a scoping review

BACKGROUND

Sensor technology could provide solutions to monitor postures and motions and to help hospital patients reach their rehabilitation goals with minimal supervision. Synthesized information on device applications and methodology is lacking.

OBJECTIVES

The purpose of this scoping review was to provide an overview of device applications and methodological approaches to monitor postures and motions in hospitalized patients using sensor technology.

METHODS

A systematic search of Embase, Medline, Web of Science and Google Scholar was completed in February 2023 and updated in March 2024. Included studies described populations of hospitalized adults with short admission periods and interventions that use sensor technology to objectively monitor postures and motions. Study selection was performed by two authors independently of each other. Data extraction and narrative analysis focused on the applications and methodological approaches of included articles using a personalized standard form to extract information on device, measurement and analysis characteristics of included studies and analyse frequencies and usage.

RESULTS

A total of 15.032 articles were found and 49 articles met the inclusion criteria. Devices were most often applied in older adults (n = 14), patients awaiting or after surgery (n = 14), and stroke (n = 6). The main goals were gaining insight into patient physical behavioural patterns (n = 19) and investigating physical behaviour in relation to other parameters such as muscle strength or hospital length of stay (n = 18). The studies had heterogeneous study designs and lacked completeness in reporting on device settings, data analysis, and algorithms. Information on device settings, data analysis, and algorithms was poorly reported.

CONCLUSIONS

Studies on monitoring postures and motions are heterogeneous in their population, applications and methodological approaches. More uniformity and transparency in methodology and study reporting would improve reproducibility, interpretation and generalization of results. Clear guidelines for reporting and the collection and sharing of raw data would benefit the field by enabling study comparison and reproduction.

Measurement properties of activity monitoring for a rehabilitation (AMoR) platform in post-stroke individuals in a simulated home environment

AIM

The aim of this study was to evaluate the measurement properties of activity monitoring for a rehabilitation (AMoR) platform for step counting, time spent in sedentary behavior, and postural changes during activities of daily living (ADLs) in a simulated home environment.

METHODS

Twenty-one individuals in the post-stroke chronic phase used the AMoR platform during an ADL protocol and were monitored by a video camera. Spearman's correlation coefficient, mean absolute percent error (MAPE), intraclass correlation coefficient (ICC), and Bland-Altman plot analyses were used to estimate the validity and reliability between the AMoR platform and the video for step counting, time spent sitting/lying, and postural changes from sit-to-stand (SI-ST) and sit-to-stand (ST-SI).

RESULTS

Validity of the platform was observed with very high correlation values for step counting (rs = 0.998) and time spent sitting/lying (rs = 0.992) and high correlation for postural change of SI-ST (rs = 0.850) and ST-SI (rs = 0.851) when compared to the video. An error percentage above 5% was observed only for the SI-ST postural change (7.13%). The ICC values show excellent agreement for step counting (ICC3, k = 0.999) and time spent sitting/lying (ICC3, k = 0.992), and good agreement for SI-ST (ICC3, k = 0.859) and ST-SI (ICC3, k = 0.936) postural change. Values of the differences for step counting, sitting/lying time, and postural change were within the limits of agreement according to the analysis of the Bland-Altman graph.

CONCLUSION

The AMoR platform presented validity and reliability for step counting, time spent sitting/lying, and identification of SI-ST and ST-SI postural changes during tests in a simulated environment in post-stroke individuals.

Validity of the activPAL and ActiGraph for measuring sitting time and steps in hospitalised orthopaedic patients with altered weight bearing

PURPOSE

To determine the criterion validity of the activPAL and ActiGraph for measuring steps and sitting/sedentary time, compared to observation, in people hospitalised following orthopaedic lower limb injury who were weight bearing (WB) (i.e., walking) or non-weight bearing (NWB) (i.e., hopping).

MATERIALS AND METHODS

Participants wore an activPAL and ActiGraph on the hip/thigh/unaffected (UA)/affected ankle (AA) while completing bouts of walking and sitting. Lin's concordance correlation coefficient, Bland-Altman methods, and ratio of agreement were used to compare device-measured to observed (videoed) step count, sitting/sedentary time.

RESULTS

In 42 participants, the ActiGraph demonstrated excellent concordance with the observed step count when worn on the ankle (LCC 0.91-0.92) compared to the hip (LCC 0.56) in participants that were WB. The ActiGraph AA achieved the highest concordance (LCC 0.71) with observed steps in participants NWB. The activPAL had poor concordance with observed steps, particularly at slow gait speeds, in participants that were WB (LCC 0.38-0.46), however was less influenced by gait speed and had good concordance in NWB participants (LCC 0.52-0.69). The activPAL (LCC 0.79-0.88) and ActiGraph UA (LCC 0.94) showed excellent concordance with observed sitting and sedentary time, respectively.

CONCLUSIONS

The ActiGraph worn at the ankle provided the most valid measure of steps in people who are WB and NWB following orthopaedic injury, while the activPAL was best for measuring sitting time.Implications for rehabilitationTo accurately measure both steps and sitting time in people with lower limb orthopaedic injuries, a combination of activity monitors should be used (i.e., ActiGraph for steps, activPAL for sitting time).The ActiGraph device when worn on the ankle demonstrated the strongest agreement with observed step count in people who were weight bearing and non-weight bearing.Caution is needed when using thigh- or hip-worn devices in people who walk slowly.

Validation of the Activ8 Activity Monitor for Monitoring Postures, Motions, Transfers, and Steps of Hospitalized Patients

Sedentary behaviors and low physical activity among hospitalized patients have detrimental effects on health and recovery. Wearable activity monitors are a promising tool to promote mobilization and physical activity. However, existing devices have limitations in terms of their outcomes and validity. The Activ8 device was optimized for the hospital setting. This study assessed the concurrent validity of the modified Activ8. Hospital patients performed an activity protocol that included basic (e.g., walking) and functional activities (e.g., room activities), with video recordings serving as the criterion method. The assessed outcomes were time spent walking, standing, upright, sedentary, and newly added elements of steps and transfers. Absolute and relative time differences were calculated, and Wilcoxon and Bland-Altman analyses were conducted. Overall, the observed relative time differences were lower than 2.9% for the basic protocol and 9.6% for the functional protocol. Statistically significant differences were detected in specific categories, including basic standing (p < 0.05), upright time (p < 0.01), and sedentary time (p < 0.01), but they did not exceed the predetermined 10% acceptable threshold. The modified Activ8 device is a valid tool for assessing body postures, motions, steps, and transfer counts in hospitalized patients. This study highlights the potential of wearable activity monitors to accurately monitor and promote PA among hospital patients.

Accelerometry applications and methods to assess standing balance in older adults and mobility-limited patient populations: a narrative review

Accelerometers provide an opportunity to expand standing balance assessments outside of the laboratory. The purpose of this narrative review is to show that accelerometers are accurate, objective, and accessible tools for balance assessment. Accelerometry has been validated against current gold standard technology, such as optical motion capture systems and force plates. Many studies have been conducted to show how accelerometers can be useful for clinical examinations. Recent studies have begun to apply classification algorithms to accelerometry balance measures to discriminate populations at risk for falls. In addition to healthy older adults, accelerometry can monitor balance in patient populations such as Parkinson's disease, multiple sclerosis, and traumatic brain injury. The lack of software packages or easy-to-use applications have hindered the shift into the clinical space. Lack of consensus on outcome metrics has also slowed the clinical adoption of accelerometer-based balance assessments. Future studies should focus on metrics that are most helpful to evaluate balance in specific populations and protocols that are clinically efficacious.

The feasibility of using a digital tool to enhance mobilisation following abdominal cancer surgery-a non-randomised controlled trial

BACKGROUND

Early mobilisation is strongly recommended following abdominal cancer surgery, but evidence on how to structure early mobilisation to improve outcomes and support patient adherence is lacking. Pedatim® (Phystec) is a novel digital tool designed to support mobilisation in hospital settings using prescribed activities and goals on a tablet. The aim of this study was to evaluate the feasibility of the Pedatim tablet to enhance mobilisation following abdominal cancer surgery.

METHODS

In a non-randomised feasibility trial design, participants were recruited between January and May 2022 at Karolinska University Hospital, Sweden. Participants used a Pedatim tablet from postoperative day 1 (POD 1) until hospital discharge. The primary objective was to evaluate process feasibility, regarding recruitment, compliance, and acceptability. Recruitment was measured by percentage of available patients included, eligibility criteria sufficiency, and number of dropouts. Compliance was measured by number of patients using versus not using the board. Acceptability was measured using the System Usability Scale. The secondary objective was to evaluate scientific feasibility, defined as an indication of treatment effects where physical activity was assessed using an activPAL accelerometer. Unforeseen events relating to the tablet were also registered.

RESULTS

Based on predetermined feasibility criteria, the overall study design was determined to be feasible regarding recruitment as 69% accepted participation (n = 20), compliance was 95%, and the acceptability mean score was high (77/100). Eligibility criteria were not feasible as 79% (n = 108) of available patients were excluded. The intervention was determined to be scientifically feasible, mean steps per day increased from 623 (SD 766) to 1823 (SD 1446), and mean sit-to-stand transitions per day increased from 11 (SD 8) to 29 (SD 12) POD 1-4. Technical issues emerged, highlighting the need for available technical support and "user champions" among healthcare professionals on the ward.

CONCLUSIONS

Using the Pedatim tablet to enhance mobilisation following abdominal cancer surgery was deemed feasible, but a randomised controlled trial is needed to determine the tool's effectiveness. The study process was determined to be feasible with revisions of the eligibility criteria needed before a future trial. Involving healthcare professionals and providing available technical support are important for future implementation.

Daily variation in physical activity during mechanical ventilation and stay in the intensive care unit

BACKGROUND

Early mobilisation of mechanically ventilated patients during their stay at an intensive care unit (ICU) can improve physical recovery. Yet, an objective and specified description of physical activities while in the ICU is lacking. Therefore, our aim was to describe the objectively assessed type, quantity, and daily variation of physical activity among mechanically ventilated patients while in the ICU.

METHOD

In an observational study in two mixed medical/surgical ICUs, we measured body posture in 39 patients on mechanical ventilation using a thigh- and chest-worn accelerometer while in the ICU. The accelerometer describes time spent lying, sitting, moving, in-bed cycling, standing and walking. Descriptive analysis of physical activity and daily variation was done using STATA.

RESULTS

We found that mechanically ventilated patients spend 20/24 h lying in bed, 3 h sitting and only 1 h standing, moving, walking or bicycling while in the ICU. Intervals of non-lying time appeared from 9.00 to 12.00 and again from 18.00 to 21.30, with peaks at the hours of 9.00 and 18.00.

CONCLUSION

ICU patients on mechanical ventilation were primarily sedentary. Physical activity of mechanically ventilated patients seems to be related to nurse- and/or physiotherapy-initiated activities. There is a need to create an awareness of improving clinical routines, towards active mobilisation throughout the day, for this vulnerable patient population during their stay in the ICU.

Accelerometer-measured Inpatient Physical Activity and Associated Outcomes after Major Abdominal Surgery: A Systematic Review (Preprint)

BACKGROUND

It remains unclear how inpatient physical activity after major abdominal surgery affects outcomes. Accelerometer research may provide further evidence for postoperative mobilization.

OBJECTIVE

We aimed to summarize the current literature evaluating the impact of accelerometer-measured postoperative physical activity on outcomes after major abdominal surgery.

METHODS

We searched PubMed and Google Scholar in October 2021 to conduct a systematic review. Studies were included if they used accelerometers to measure inpatient physical behaviors immediately after major abdominal surgery, defined as any nonobstetric procedures performed under general anesthesia requiring hospital admission. Studies were eligible only if they evaluated the effects of physical activity on postoperative outcomes such as postoperative complications, return of gastrointestinal function, hospital length of stay, discharge destination, and readmissions. We excluded studies involving participants aged <18 years. Risk of bias was assessed using the risk-of-bias assessment tool for nonrandomized studies (RoBANS) for observational studies and the revised Cochrane risk-of-bias tool for randomized trials (RoB 2) for randomized controlled trials (RCTs). Findings were summarized by qualitative synthesis.

RESULTS

We identified 15 studies. Risk of bias was high in 14 (93%) of the 15 studies. Most of the studies (11/15, 73%) had sample sizes of <100. Of the 15 studies, 13 (87%) included the general surgery population, 1 (7%) was a study of patients who had undergone gynecologic surgery, and 1 (7%) included a mixed (abdominal, thoracic, gynecologic, and orthopedic) surgical population. Of the 15 studies, 12 (80%) used consumer-grade accelerometers to measure physical behaviors. Step count was the most commonly reported physical activity outcome (12/15, 80%). In the observational studies (9/15, 60%), increased physical activity during the immediate postoperative period was associated with earlier return of gastrointestinal function, fewer surgical and pulmonary complications, shorter hospital length of stay, and fewer readmissions. In the RCTs (6/15, 40%), only 1 (17%) of the 6 studies demonstrated improved outcomes (shorter time to flatus and hospital length of stay) when a mobility-enhancing intervention was compared with usual care. Notably, mobility-enhancing interventions used in 4 (67%) of the 6 RCTs did not result in increased postoperative physical activity.

CONCLUSIONS

Although observational studies show strong associations between postoperative physical activity and outcomes after major abdominal surgery, RCTs have not proved the benefit of mobility-enhancing interventions compared with usual care. The overall risk of bias was high, and we could not synthesize specific recommendations for postoperative mobilization. Future research would benefit from improving study design, increasing methodologic rigor, and measuring physical behaviors beyond step counts to understand the impact of postoperative mobilization on outcomes after major abdominal surgery.

Identification and Quantification of Activities Common to Intensive Care Patients; Development and Validation of a Dual-Accelerometer-Based Algorithm

The aim of this study was to develop and validate an algorithm that can identify the type, frequency, and duration of activities common to intensive care (IC) patients. Ten healthy participants wore two accelerometers on their chest and leg while performing 14 activities clustered into four protocols (i.e., natural, strict, healthcare provider, and bed cycling). A video served as the reference standard, with two raters classifying the type and duration of all activities. This classification was reliable as intraclass correlations were all above 0.76 except for walking in the healthcare provider protocol, (0.29). The data of four participants were used to develop and optimize the algorithm by adjusting body-segment angles and rest-activity-threshold values based on percentage agreement (%Agr) with the reference. The validity of the algorithm was subsequently assessed using the data from the remaining six participants. %Agr of the algorithm versus the reference standard regarding lying, sitting activities, and transitions was 95%, 74%, and 80%, respectively, for all protocols except transitions with the help of a healthcare provider, which was 14-18%. For bed cycling, %Agr was 57-76%. This study demonstrated that the developed algorithm is suitable for identifying and quantifying activities common for intensive care patients. Knowledge on the (in)activity of these patients and their impact will optimize mobilization.

Physical activity monitoring during hospital stay: a validation study

PURPOSE

The primary aim of this study was to investigate the concurrent validity of the PAM AM400 accelerometer for measuring physical activity in usual care in hospitalized patients by comparing it with the ActiGraph wGT3X-BT accelerometer.

MATERIALS AND METHODS

This was a prospective single centre observational study performed at the University Medical Centre Utrecht in The Netherlands. Patients admitted to different clinical wards were included. Intraclass Correlation Coefficients (ICCs) were computed using a two-way mixed model with random subjects. Additionally, Bland-Altman plots were made to visualize the level of agreement of the PAM with the ActiGraph. To test for proportional bias, a regression analysis was performed.

RESULTS

In total 17 patients from different clinical wards were included in the analyses. The level of agreement between the PAM and ActiGraph was found strong with an ICC of 0.955. The Bland-Altman analyses showed a mean difference of 1.12 min between the two accelerometers and no proportional bias (p = 0.511).

CONCLUSIONS

The PAM is a suitable movement sensor to validly measure the active minutes of hospitalized patients. Implementation of this device in daily care might be helpful to change the immobility culture in hospitals.IMPLICATIONS FOR REHABILITATIONPhysical inactivity is common during hospital admission and the main cause of loss of muscle mass and physical fitness.The PAM AM400 is a suitable movement sensor to validly measure the active minutes of hospitalized patients.Implementation of this device in daily care might be helpful to change the immobility culture in hospitals.

Progressing to Objective Measures of Daily Mobility in Hospitalized Older Adults

Accurate mobility assessment of hospitalized older adults is necessary to aid nurses in planning and providing appropriate mobility support; however, nurses cite lack of resources and time limitations as barriers. Accelerometry enables a detailed objective measurement of predominant hospital mobility activities in the older adult population, such as percent time sitting, and the sit-to-stand (STS) transition. The current exploratory study examined the use of a novel, unobtrusive accelerometry technique to obtain postural and STS metrics on 27 older adults during their hospital stay. Total device wear time in the hospital was 96.2%. Participants spent 60.3% time lying, 20.3% time sitting, 5.3% time standing, and 2% time stepping during hospitalization, and, on average, completed the STS transition 20 times (SD = 13) per 24-hour period. There were no participant complaints about wearing the device. Our exploratory study shows accelerometry provides automated, continuous data and may support accurate nursing assessment of patient mobility. [Journal of Gerontological Nursing, 48(5), 35-41.].

Fine Detection of Human Motion During Activities of Daily Living as a Clinical Indicator for the Detection and Early Treatment of Chronic Diseases: The E-Mob Project

Methods to measure physical activity and sedentary behaviors typically quantify the amount of time devoted to these activities. Among patients with chronic diseases, these methods can provide interesting behavioral information, but generally do not capture detailed body motion and fine movement behaviors. Fine detection of motion may provide additional information about functional decline that is of clinical interest in chronic diseases. This perspective paper highlights the need for more developed and sophisticated tools to better identify and track the decomposition, structuration, and sequencing of the daily movements of humans. The primary goal is to provide a reliable and useful clinical diagnostic and predictive indicator of the stage and evolution of chronic diseases, in order to prevent related comorbidities and complications among patients.

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.

Sedentary Time in Older Adults With Acute Cardiovascular Disease

Background

Older adults may be subject to prolonged bedrest during hospitalization for acute cardiovascular disease, which can contribute to poor functional outcomes posthospitalization. Our objective was to describe mobility status in hospitalized older adults with acute cardiovascular disease.

Methods

Patients aged ≥ 60 years old in the cardiac intensive care unit and cardiovascular ward at a tertiary care academic centre in Montréal, Québec were prospectively enrolled from April 2019 to March 2020. Activity levels were measured with the ActiGraph GT9X Link 3-axis accelerometer (ActiGraph, Pensacola, FL). Sedentary was defined as lying in bed or in a sitting position. Health-related quality of life (HRQOL) was measured with the Short-Form 36 (SF-36) questionnaire by telephone at 1 month posthospitalization. The primary outcome was percentage of sedentary time during hospitalization.

Results

There were 35 patients included in the analysis (75.7 ± 6.9 years old; 45.7% female; 22.9% ischemic heart disease; 20.0% heart failure). Patients spent 91.2% ± 5.5 in a sedentary position during their hospital stay. Mean steps per minute were 1.0 ± 1.2, and mean kcals consumed per day were 116.6 ± 124.5. In the multivariable analysis, a higher percentage of sedentary time and lower steps per minute were each associated with lower total SF-36 scores at 1-month posthospitalization (both P < 0.05).

Conclusions

Older adults with acute cardiovascular disease may be sedentary for a large part of their hospital stay. Increased sedentary time is associated with worse self-reported posthospital HRQOL. Future studies are needed to determine whether interventions to increase activity during hospitalization improve posthospital HRQOL and functional outcomes.

Evaluating the Validity and Utility of Wearable Technology for Continuously Monitoring Patients in a Hospital Setting: Systematic Review

BACKGROUND

The term posthospital syndrome has been used to describe the condition in which older patients are transiently frail after hospitalization and have a high chance of readmission. Since low activity and poor sleep during hospital stay may contribute to posthospital syndrome, the continuous monitoring of such parameters by using affordable wearables may help to reduce the prevalence of this syndrome. Although there have been systematic reviews of wearables for physical activity monitoring in hospital settings, there are limited data on the use of wearables for measuring other health variables in hospitalized patients.

OBJECTIVE

This systematic review aimed to evaluate the validity and utility of wearable devices for monitoring hospitalized patients.

METHODS

This review involved a comprehensive search of 7 databases and included articles that met the following criteria: inpatients must be aged >18 years, the wearable devices studied in the articles must be used to continuously monitor patients, and wearables should monitor biomarkers other than solely physical activity (ie, heart rate, respiratory rate, blood pressure, etc). Only English-language studies were included. From each study, we extracted basic demographic information along with the characteristics of the intervention. We assessed the risk of bias for studies that validated their wearable readings by using a modification of the Consensus-Based Standards for the Selection of Health Status Measurement Instruments.

RESULTS

Of the 2012 articles that were screened, 14 studies met the selection criteria. All included articles were observational in design. In total, 9 different commercial wearables for various body locations were examined in this review. The devices collectively measured 7 different health parameters across all studies (heart rate, sleep duration, respiratory rate, oxygen saturation, skin temperature, blood pressure, and fall risk). Only 6 studies validated their results against a reference device or standard. There was a considerable risk of bias in these studies due to the low number of patients in most of the studies (4/6, 67%). Many studies that validated their results found that certain variables were inaccurate and had wide limits of agreement. Heart rate and sleep were the parameters with the most evidence for being valid for in-hospital monitoring. Overall, the mean patient completion rate across all 14 studies was >90%.

CONCLUSIONS

The included studies suggested that wearable devices show promise for monitoring the heart rate and sleep of patients in hospitals. Many devices were not validated in inpatient settings, and the readings from most of the devices that were validated in such settings had wide limits of agreement when compared to gold standards. Even some medical-grade devices were found to perform poorly in inpatient settings. Further research is needed to determine the accuracy of hospitalized patients' digital biomarker readings and eventually determine whether these wearable devices improve health outcomes.

Physical, motivational and environmental factors influencing physical activity promotion during hospitalization: Older patients' perspective

Better understanding of older patients' perspective on physical, motivational and environmental barriers and enablers in physical activity promotion during hospitalization contributes to the development of strategies to increase in hospital physical activity. Using a mixed method approach, barriers and enablers from patients (in)dependent in physical activity (Functional Ambulation Categories ≥4 versus <4) were identified. Forty-nine patients (median age 77 years IQR:75-83, female: n = 25) were interviewed. Barriers reported as most important were feeling weak (n = 10), having lines/drains (n = 9) and pain (n = 7) and enablers reported as most important were feeling physically independent (n = 19), sense of importance of physical activity (n = 12), and maintaining physical strength (n = 10). Physically dependent patients were more frequently encouraged by professionals to be physically active compared to independent patients. Focus on physical barriers and motivational enablers for older patients may help to increase their physical activity during hospitalization and encouragement by health care professionals should also encompass physically independent patients.

Optimization and Validation of a Classification Algorithm for Assessment of Physical Activity in Hospitalized Patients

Low amounts of physical activity (PA) and prolonged periods of sedentary activity are common in hospitalized patients. Objective PA monitoring is needed to prevent the negative effects of inactivity, but a suitable algorithm is lacking. The aim of this study is to optimize and validate a classification algorithm that discriminates between sedentary, standing, and dynamic activities, and records postural transitions in hospitalized patients under free-living conditions. Optimization and validation in comparison to video analysis were performed in orthopedic and acutely hospitalized elderly patients with an accelerometer worn on the upper leg. Data segmentation window size (WS), amount of PA threshold (PA Th) and sensor orientation threshold (SO Th) were optimized in 25 patients, validation was performed in another 25. Sensitivity, specificity, accuracy, and (absolute) percentage error were used to assess the algorithm’s performance. Optimization resulted in the best performance with parameter settings: WS 4 s, PA Th 4.3 counts per second, SO Th 0.8 g. Validation showed that all activities were classified within acceptable limits (>80% sensitivity, specificity and accuracy, ±10% error), except for the classification of standing activity. As patients need to increase their PA and interrupt sedentary behavior, the algorithm is suitable for classifying PA in hospitalized patients.

Developing and validating an accelerometer-based algorithm with machine learning to classify physical activity after acquired brain injury

Purpose: To develop and validate an accelerometer-based algorithm classifying physical activity in people with acquired brain injury (ABI) in a laboratory setting resembling a real home environment.Materials and methods: A development and validation study was performed. Eleven healthy participants and 25 patients with ABI performed a protocol of transfers and ambulating activities. Activity measurements were performed with accelerometers and with thermal video camera as gold standard reference. A machine learning-based algorithm classifying specific physical activities from the accelerometer data was developed and cross-validated in a training sample of 11 healthy participants. Criterion validity of the algorithm was established in 3 models classifying the same protocol of activities in people with ABI.Results: Modeled on data from 11 healthy and 15 participants with ABI, the algorithm had a good precision for classifying transfers and ambulating activities in data from 10 participants with ABI. The weighted sensitivity for all activities was 89.3% (88.3-90.4%) and the weighted positive predictive value was 89.7% (88.7-90.7%). The algorithm differentiated between lying and sitting activities.Conclusion: An algorithm to classify physical activities in populations with ABI was developed and its criterion validity established. Further testing of precision in home settings with continuous activity monitoring is warranted.

Validity of a Non-Proprietary Algorithm for Identifying Lying Down Using Raw Data from Thigh-Worn Triaxial Accelerometers

Body postural allocation during daily life is important for health, and can be assessed with thigh-worn accelerometers. An algorithm based on sedentary bouts from the proprietary ActivePAL software can detect lying down from a single thigh-worn accelerometer using rotations of the thigh. However, it is not usable across brands of accelerometers. This algorithm has the potential to be refined. Aim: To refine and assess the validity of an algorithm to detect lying down from raw data of thigh-worn accelerometers. Axivity-AX3 accelerometers were placed on the thigh and upper back (reference) on adults in a development dataset (n = 50) and a validation dataset (n = 47) for 7 days. Sedentary time from the open Acti4-algorithm was used as input to the algorithm. In addition to the thigh-rotation criterion in the existing algorithm, two criteria based on standard deviation of acceleration and a time duration criterion of sedentary bouts were added. The mean difference (95% agreement-limits) between the total identified lying time/day, between the refined algorithm and the reference was +2.9 (−135,141) min in the development dataset and +6.5 (−145,159) min in the validation dataset. The refined algorithm can be used to estimate lying time in studies using different accelerometer brands.

Hip Positioning and Sitting Posture Recognition Based on Human Sitting Pressure Image

Bad sitting posture is harmful to human health. Intelligent sitting posture recognition algorithm can remind people to correct their sitting posture. In this paper, a sitting pressure image acquisition system was designed. With the system, we innovatively proposed a hip positioning algorithm based on hip templates. The average deviation of the algorithm for hip positioning is 1.306 pixels (the equivalent distance is 1.50 cm), and the proportion of the maximum positioning deviation less than three pixels is 94.1%. Statistics show that the algorithm works relatively well for different subjects. At the same time, the algorithm can not only effectively locate the hip position with a small rotation angle (0°–15°), but also has certain adaptability to the sitting posture with a medium rotation angle (15°–30°) or a large rotation angle (30°–45°). Using the hip positioning algorithm, the regional pressure values of the left hip, right hip and caudal vertebrae are effectively extracted as the features, and support vector machine (SVM) with polynomial kernel is used to classify the four types of sitting postures, with a classification accuracy of up to 89.6%.

Levels of Physical Activity and Sedentary Behavior During and After Hospitalization: A Systematic Review

OBJECTIVES

To systematically review and synthesize the evidence on physical activity and sedentary behavior during and after hospitalization.

DATA SOURCES

Electronic databases and reference lists of relevant articles were searched from 2000 to April 2020.

STUDY SELECTION

Studies which continuously monitored physical activity and/or sedentary behavior in hospitalized adults across 2 settings (ie, without a break in measurement between settings). Monitoring could occur from an acute to a subacute or rehabilitation hospital setting, an acute setting to home, or from a subacute or rehabilitation setting to home.

DATE EXTRACTION

Data extraction and methodological quality assessments were independently performed by 2 reviewers using standardized checklists.

DATA SYNTHESIS

A total of 15 of the 5579 studies identified were included. The studies were composed of heterogenous patient populations. All studies monitored patients with either an accelerometer and/or pedometer and reported a variety of measures, including steps per day, sedentary time, and activity counts. The majority of studies (12 of 15) showed that patients engaged in 1.3 to 5.9 times more physical activity and up to 67% less daily sedentary behavior at home after discharge from acute or subacute settings.

CONCLUSIONS

Patients engaged in more physical activity and less sedentary behavior at home compared to both the acute and subacute hospital settings. This may reflect the natural course of recovery or the effect of setting on activity levels. Enabling early discharge home through the implementation of home-hospitalization models may result in increased patient physical activity and reduced sedentary behavior. Further experimental studies are required investigating the effect of home-based models of care on physical activity and sedentary behavior.

Core Domains for Research on Hospital Inactivity in Acutely Ill Older Adults: A Delphi Consensus Study

OBJECTIVE

To identify core domains for research studies of physical activity and sedentary behavior during hospitalization for older adults with an acute medical illness.

DESIGN

A 4-Round Delphi consensus process. Round 1 invited responses to open-ended questions to generate items for the core domains research. In rounds 2-4, participants were invited to use a Likert scale (1-9) to rate the importance of each core domain for research studies of physical activity and/or sedentary behavior in hospitalized older adults with an acute medical illness.

SETTING

Online surveys.

PARTICIPANTS

A total of 49 participants were invited to each round (international researchers, clinicians, policy makers and patients). Response rates across rounds 1-4 were 94%, 88%, 83% and 81%, respectively.

INTERVENTIONS

None.

MAIN OUTCOME MEASURES

Consensus was defined a priori as ≥70% of respondents rating an item as "critical" (score≥7) and ≤15% of respondents rating an item as "not important" (score≤3).

RESULTS

In round 2, a total of 9 of 25 core domains reached consensus agreement (physical functioning, general, role functioning, emotional functioning, global quality of life, hospital, psychiatric, cognitive functioning, carer burden). In round 3, an additional 8 reached consensus (adverse events, perceived health status, musculoskeletal, social functioning, vascular, cardiac, mortality, economic). Round 4 participants provided further review and a final rating of all 17 core domains that met consensus in previous rounds. Four core domains were rated as "critically important" to evaluate: physical functioning, social functioning, emotional functioning, and hospital outcomes.

CONCLUSIONS

This preliminary work provides international and expert consensus-based core domains for development toward a core-outcome set for research, with the ultimate goal of fostering consistency in outcomes and reporting to accelerate research on effective strategies to address physical activity and/or sedentary behavior in older adults while hospitalized.

Mobility levels of acute medical patients: Is behavioural mapping comparable to accelerometry?

OBJECTIVE

To (1) determine agreement between behavioural mapping and accelerometry for measuring mobility levels in an acute medical inpatient setting and to (2) explore and compare the required resources and costs for both methods.

DESIGN

Observational cross-sectional study.

SETTING

Tertiary referral teaching hospital in Brisbane, Australia.

SUBJECTS

Adult patients admitted to two acute medical wards.

MAIN MEASURES

Mobility levels were recorded by behavioural mapping, and thigh and chest-worn accelerometers (ActivPAL). The level of agreement between the two methods was evaluated using the Intraclass Correlation Coefficients for each mobility level (i.e. lying, sitting, upright, standing and walking).

RESULTS

Nineteen patients (10 male (53%); mean(SD) age of 72(14) years) were included in the agreement analysis. The Intraclass Correlation Coefficients were high for 'lying' (ICC = 0.87), 'sitting' (ICC = 0.84) and 'upright' (ICC = 0.93), indicating good to excellent agreement between the two methods. For these mobility levels, mean differences between the two methods were small (<2%), with large standard deviations (up to 18%). Agreement was poor for 'standing' (ICC = 0.00) and 'walking' (ICC = 0.35). Both methods were labour-intensive, with labour costs of A$1,285/€798 (34 hours) for behavioural mapping and A$1,055/€655 (28 hours) for accelerometry. No further costs were involved in behavioural mapping, but clinical backfill was required. Accelerometry involved a financial investment for accelerometers (A$11,100/€6,894 for 22 ActivPAL devices).

CONCLUSION

Agreement between behavioural mapping and accelerometry was good for measuring 'lying', 'sitting' and 'upright', but poor for 'standing' and 'walking' in an acute inpatient setting. Both behavioural mapping and accelerometry were labour-intensive, with high costs for the accelerometry equipment.

Patient-centred measurement of recovery from day-case surgery using wrist worn accelerometers: a pilot and feasibility study

This pilot and feasibility study evaluated wrist-worn accelerometers to measure recovery from day-case surgery in comparison with daily quality of recovery-15 scores. The protocol was designed with extensive patient and public involvement and engagement, and delivered by a research network of anaesthesia trainees. Forty-eight patients recruited through pre-operative assessment clinics wore wrist accelerometers for 7 days before (pre-operative) and immediately after elective surgery (early postoperative), and again at 3 months (late postoperative). Validated activity and quality of recovery questionnaires were administered. Raw accelerometry data were archived and analysed using open source software. The mean (SD) number of valid days of accelerometer wear per participant in the pre-operative, early and late postoperative periods were 5.4 (1.7), 6.6 (1.1) and 6.6 (1.0) days, respectively. On the day after surgery, Euclidian norm minus one (a summary measure of raw accelerations), step count, light physical activity and moderate/vigorous physical activity decreased to 57%, 47%, 59% and 35% of baseline values, respectively. Activity increased progressively on a daily basis but had not returned to baseline values by 7 days. Patient questionnaires suggested subjective recovery by postoperative day 3 to 4; however, accelerometry data showed that activity levels had not returned to baseline at this point. All activity measures had returned to baseline by 3 months. Wrist-worn accelerometery is acceptable to patients and feasible as a surrogate measure for monitoring postoperative recovery from day-case surgery. Our results suggest that patients may overestimate their rate of recovery from day-case surgery, which has important implications for future research.

A scoping review of interventions using accelerometers to measure physical activity or sedentary behaviour during hospitalization

Objective:

To identify interventions using wearable accelerometers to measure physical activity and/or sedentary behaviour in adults during hospitalization for an acute medical/surgical condition.

Data sources:

Four databases were searched in August 2019 (MEDLINE, CINAHL, Scopus, EMBASE).

Review methods:

Studies were selected if they described an intervention in adults with a medical/surgical condition, and concurrently reported an accelerometer-derived measure of physical activity and/or sedentary behaviour while participants were admitted. Items were screened for eligibility in duplicate. Included studies were synthesized to describe intervention types, feasibility and potential effectiveness.

Results:

Twenty-two studies were included, reporting on 3357 participants (2040 with accelerometer data). Identified types of interventions were: pre-habilitation ( n = 2) exercise ( n = 3), patient behaviour change with self-monitoring ( n = 6), models of care ( n = 5), implementing system change ( n = 2), surgical technique ( n = 2) patients wearing day clothes ( n = 1) and education about activity in hospital ( n = 1). Of 16 studies that reported intervention effects on physical activity, 11 reported a favourable impact including studies of: pre-habilitation, self-monitoring (accelerometry or an activity whiteboard), physiotherapy, an early mobility bundle, minimally invasive surgery, an education booklet and by implementing system change. Of the six studies that reported intervention effects on sedentary behaviour, there was a favourable impact with an activity whiteboard, models of care and an education booklet.

Conclusion:

Accelerometer-derived measures of physical activity and/or sedentary behaviour have been used to describe sample characteristics and intervention effects in studies of hospitalized adults. Interventions may involve a range of health professionals, but less is known about sedentary behaviour in this setting.

Recommendations for older adults' physical activity and sedentary behaviour during hospitalisation for an acute medical illness: an international Delphi study

BACKGROUND

Immobility is major contributor to poor outcomes for older people during hospitalisation with an acute medical illness. Yet currently there is no specific mobility guidance for this population, to facilitate sustainable changes in practice. This study aimed to generate draft physical activity (PA) and sedentary behaviour (SB) recommendations for older adults' during hospitalisation for an acute medical illness.

METHODS

A 4-Round online Delphi consensus survey was conducted. International researchers, medical/nursing/physiotherapy clinicians, academics from national PA/SB guideline development teams, and patients were invited to participate. Round 1 sought responses to open-ended questions. In Rounds 2-3, participants rated the importance of items using a Likert scale (1-9); consensus was defined a priori as: ≥70% of respondents rating an item as "critical" (score ≥ 7) and ≤ 15% of respondents rating an item as "not important" (score ≤ 3). Round 4 invited participants to comment on draft statements derived from responses to Rounds 1-3; Round 4 responses subsequently informed final drafting of recommendations.

RESULTS

Forty-nine people from nine countries were invited to each Round; response rates were 94, 90, 85 and 81% from Rounds 1-4 respectively. 43 concepts (items) from Rounds 2 and 3 were incorporated into 29 statements under themes of PA, SB, people and organisational factors in Round 4. Examples of the final draft recommendations (being the revised version of statements with highest participant endorsement under each theme) were: "some PA is better than none", "older adults should aim to minimise long periods of uninterrupted SB during waking hours while hospitalised", "when encouraging PA and minimising SB, people should be culturally responsive and mindful of older adults' physical and mental capabilities" and "opportunities for PA and minimising SB should be incorporated into the daily care of older adults with a focus on function, independence and activities of daily living".

CONCLUSIONS

These world-first consensus-based statements from expert and stakeholder consultation provide the starting point for recommendations to address PA and SB for older adults hospitalised with an acute medical illness. Further consultation and evidence review will enable validation of these draft recommendations with examples to improve their specificity and translation to clinical practice.

Construct Validity of the Chilean-Spanish Version of the Functional Status Score for the Intensive Care Unit: A Prospective Observational Study Using Actigraphy in Mechanically Ventilated Patients

OBJECTIVE

To evaluate the construct validity (hypotheses testing) of the Chilean-Spanish version of the Functional Status Score for the Intensive Care Unit (FSS-ICU) using continuous actigraphy from intensive care unit (ICU) admission to ICU discharge.

DESIGN

The Chilean-Spanish version of the FSS-ICU was used in a prospective observational study to mainly evaluate its correlation with actigraphy variables. The FSS-ICU was assessed on awakening and at ICU discharge, while actigraphy variables were recorded from ICU admission to ICU discharge.

SETTING

A 12-bed academic medical-surgical ICU.

PARTICIPANTS

Mechanically ventilated patients (N=30), of 92 patients screened.

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURES

Construct validity of the FSS-ICU Chilean-Spanish version was assessed by testing 12 hypotheses, including the correlation with activity counts, activity time (>99 counts/min), inactivity time (0-99 counts/min), muscle strength, ICU length of stay, and duration of mechanical ventilation.

RESULTS

The median FSS-ICU was 19 points (interquartile range [IQR], 10-26 points) on awakening and 28.5 points (IQR, 22-32 points) at ICU discharge. There was no floor/ceiling effect of the FSS-ICU at awakening (0%/0%) and only a ceiling effect at ICU discharge that was acceptable (0%/10%). Less activity time was associated with better mobility on the FSS-ICU at both awakening (ρ=-0.62, P<.001) and ICU discharge (ρ=-0.79, P<.001). Activity counts and activity time were not correlated as expected with the FSS-ICU.

CONCLUSIONS

The Chilean-Spanish FSS-ICU had a strong correlation with inactivity time during the ICU stay. These findings enhance the available clinimetric properties of the FSS-ICU.

Quantifying Mobility in the ICU: Comparison of Electronic Health Record Documentation and Accelerometer-Based Sensors to Clinician-Annotated Video

Supplemental Digital Content is available in the text.

To compare the accuracy of electronic health record clinician documentation and accelerometer-based sensors with a gold standard dataset derived from clinician-annotated video to quantify early mobility activities in adult ICU patients.

Exploring barriers to physical activity of patients at the internal medicine and surgical wards: a retrospective analysis of continuously collected data

PURPOSE

To analyse physical activity of patients during their hospital stay and to explore the relationship between physical activity and barriers to physical activity.

METHODS

This was a secondary analysis of physical activity data for patients admitted to the internal medicine and surgical wards. Physical activity data, collected with a wireless patch sensor, was operationalized as time spent lying, sitting/standing, and walking. Barriers to physical activity included patients' pain levels, the use of urinary catheters, intravenous tubing, oxygen lines, drains, and level of dependence. Regression analysis explored the relationship between physical activity and barriers to physical activity.

RESULTS

Physical activity data were collected in 39 patients (aged 27-88, mean 54 years) during hospital stay. Patients were admitted for a median of 10 d (interquartile range [IQR]: 7-15 d). These patients were lying for a median of 12.1 h (7.6-17.7), sitting/standing 11.8 h (6.3-15.7), and walking 0.1 h (0-0.3) per day. Time lying during the day related to pain levels (β = 0.4 h per unit increase in pain, p < 0.01) and drain use (β = 3.1 h, p < 0.01).

CONCLUSIONS

Patients spent the most time during the hospital stay lying in bed. Improved pain management and decreased drain use may be worth exploring to increase inpatient physical activity.Implications for rehabilitationContinuous monitoring of physical activity in patients during hospital stay is an important tool for health care professionals to improve multidisciplinary care and rehabilitation.Health care professionals should be aware of the necessity of adequate pain management and critically review the use of drains in order to improve physical activity of patients during hospital stay.Patients need extra support of health care professionals to increase physical activity during consecutive days of their hospital stay.

Validity of three accelerometers to investigate lying, sitting, standing and walking

Background

Hospital stays are associated with high levels of sedentary behavior and physical inactivity. To objectively investigate physical behavior of hospitalized patients, these is a need for valid measurement instruments. The aim of this study was to assess the criterion validity of three accelerometers to measure lying, sitting, standing and walking.

Methods

This cross-sectional study was performed in a university hospital. Participants carried out several mobility tasks according to a structured protocol while wearing three accelerometers (ActiGraph GT9X Link, Activ8 Professional and Dynaport MoveMonitor). The participants were guided through the protocol by a test leader and were recorded on video to serve as reference. Sensitivity, specificity, positive predictive values (PPV) and negative predictive values (NPV) were determined for the categories lying, sitting, standing and walking.

Results

In total 12 subjects were included with a mean age of 49.5 (SD 21.5) years and a mean body mass index of 23.8 kg/m² (SD 2.4). The ActiGraph GT9X Link showed an excellent sensitivity (90%) and PPV (98%) for walking, but a poor sensitivity for sitting and standing (57% and 53%), and a poor PPV (43%) for sitting. The Activ8 Professional showed an excellent sensitivity for sitting and walking (95% and 93%), excellent PPV (98%) for walking, but no sensitivity (0%) and PPV (0%) for lying. The Dynaport MoveMonitor showed an excellent sensitivity for sitting (94%), excellent PPV for lying and walking (100% and 99%), but a poor sensitivity (13%) and PPV (19%) for standing.

Conclusions

The validity outcomes for the categories lying, sitting, standing and walking vary between the investigated accelerometers. All three accelerometers scored good to excellent in identifying walking. None of the accelerometers were able to identify all categories validly.

Measuring physical activity levels in hospitalized patients: a comparison between behavioural mapping and data from an accelerometer

Objective:

To investigate the level of agreement of the behavioural mapping method with an accelerometer to measure physical activity of hospitalized patients.

Design:

A prospective single-centre observational study.

Setting:

A university medical centre in the Netherlands.

Subjects:

Patients admitted to the hospital.

Main measures:

Physical activity of participants was measured for one day from 9 AM to 4 PM with the behavioural mapping method and an accelerometer simultaneously. The level of agreement between the percentages spent lying, sitting and moving from both measures was evaluated using the Bland–Altman method and by calculating Intraclass Correlation Coefficients.

Results:

In total, 30 patients were included. Mean (±SD) age was 63.0 (16.8) years and the majority of patients were men (n = 18). The mean percentage of time (SD) spent lying was 47.2 (23.3) and 49.7 (29.8); sitting 42.6 (20.5) and 40.0 (26.2); and active 10.2 (6.1) and 10.3 (8.3) according to the accelerometer and observations, respectively. The Intraclass Correlation Coefficient and mean difference (SD) between the two measures were 0.852 and –2.56 (19.33) for lying; 0.836 and 2.60 (17.72) for sitting; and 0.782 and −0.065 (6.23) for moving. The mean difference between the two measures is small (⩽2.6%) for all three physical activity levels. On patient level, the variation between both measures is large with differences above and below the mean of ⩾20% being common.

Conclusion:

The overall level of agreement between the behavioural mapping method and an accelerometer to identify the physical activity levels ‘lying’, ‘sitting’ and ‘moving’ of hospitalized patients is reasonable.

A study investigating the validity of an accelerometer in quantification of step count in adult hospital inpatients recovering from critical illness

OBJECTIVE

To determine the validity of the ActiGraph GT3X accelerometer in step count quantification when compared to observed step count in hospitalised adults recovering from critical illness.

SETTING

Large National Health Service (NHS) Hospitals Trust.

SUBJECTS

In total, 20 hospital ward-based adults (age: mean 62.3, SD 11.5) who had required greater than 48 hours of mechanical ventilation in the intensive care unit.

MAIN MEASURES

Participants walked self-selected distances and speeds as part of a semi-structured movement protocol not exceeding 3 hours. Two ActiGraph GT3X accelerometers were worn, one on the thigh and one on the ankle of the non-dominant leg. Accelerometer-recorded step counts were compared against observed step counts.

RESULTS

In total, 31 separate walking episodes were analysed. A mean (SD) of 45.87 (±19.72) steps was calculated for observed step count (range 15-90). Mean differences (95% limits of agreement) of -0.84 steps (-3.88 to 2.2) for the ankle placement and -17.7 steps (-40.63 to 5.25) for the thigh were calculated. Intraclass correlation coefficients (95% confidence intervals) of 0.99 (0.99 to 1.0) and 0.46 (-0.1 to 0.78) were determined for the ankle and thigh, respectively. Placement sites were well tolerated by 95% of participants.

CONCLUSION

An ankle-mounted ActiGraph GT3X accelerometer demonstrates validity in quantification of step count in hospitalised adults recovering from critical illness. A thigh placement was not considered valid.

Validation of a wireless patch sensor to monitor mobility tested in both an experimental and a hospital setup: A cross-sectional study

Purpose

To assess the concurrent validity of a wireless patch sensor to monitor time lying, sitting/standing, and walking in an experimental and a hospital setup.

Methods

Healthy adults participated in two testing sessions: an experimental and real-world hospital setup. Data on time lying, sitting/standing, and walking was collected with the HealthPatch and concurrent video recordings. Validity was assessed in three ways: 1. test for mean differences between HealthPatch data and reference values; 2. Intraclass Correlation Coefficient analysis (ICC 3.1 agreement); and 3. test for mean differences between posture detection accuracies.

Results

Thirty-one males were included. Significant mean differences were found between HealthPatch data and reference values for sitting/standing (mean 14.4 minutes, reference: 12.0 minutes, p<0.01) and walking (mean 6.4 minutes, reference: 9.0 minutes, p<0.01) in the experimental setup. Good correlations were found between the HealthPatch data and video data for lying (ICC: 0.824) and sitting/standing (ICC: 0.715) in the hospital setup. Posture detection accuracies of the HealthPatch were significantly higher for lying and sitting/standing in the experimental setup.

Conclusions

Overall, the results show a good validity of the HealthPatch to monitor lying and poor validity to monitor sitting/standing or walking. In addition, the validity outcomes were less favourable in the hospital setup.