Review of accelerometry for determining daily activity among elderly patients

Daily steps, walking tests, and functioning in chronic stroke; comparing independent walkers to device-users

BACKGROUND AND PURPOSE

Community mobility post-stroke is important for gaining independence in daily activities. Walking devices can facilitate mobility, but it remains unclear whether individuals who use a walking device walk as many daily steps as those who do not require a device. It is also unclear whether these groups differ in their independence in daily living. This study aimed (1) to compare daily steps, walking tests, and independence in basic and instrumental activities of daily living (IADL) six months post-stroke between individuals who walk independently and individuals who use a walking device, (2) within each group to assess correlations between daily steps and walking tests, independence in basic and IADL.

METHODS

Thirty-seven community-dwelling individuals with chronic stroke; 22 participants used a walking-device and 15 participants walked independently. Daily steps were calculated as a 3-day mean by hip accelerometers. Clinical walking tests included the 10-m-walk-test, Timed Up & Go and 'Walking While Talking'. Daily living was assessed using the Functional-Independence Measure and the IADL questionnaire.

RESULTS

Daily steps of the device-users were significantly lower than the independent-walkers (195-8068 versus 147-14010 steps/day) but independence in daily living was not significantly different. Different walking tests correlated with daily steps for device-users and independent-walkers.

CONCLUSIONS

This preliminary investigation in chronic stroke revealed that device-users walk significantly fewer daily steps but are as independent in daily living as independent-walkers. Clinicians should differentiate between individuals with and without a walking device and the use of different clinical walking tests to explain daily steps should be considered. Further research is needed to assess the impact of a walking device post-stroke.

The Problem of Monitoring Activities of Older People in Multi-Resident Scenarios: An Innovative and Non-Invasive Measurement System Based on Wearables and PIR Sensors

This paper presents an innovative multi-resident activity detection sensor network that uses the Bluetooth Low Energy (BLE) signal emitted by tags worn by residents and passive infrared (PIR) motion sensors deployed in the house to locate residents and monitor their activities. This measurement system solves the problem of monitoring older people and measuring their activities in multi-resident scenarios. Metrics are defined to analyze and interpret the collected data to understand daily habits and measure the activity level (AL) of older people. The accuracy of the system in detecting movements and discriminating residents is measured. As the sensor-to-person distance increases, the system decreases its ability to detect small movements, while still being able to detect large ones. The accuracy in discriminating the identity of residents can be improved by up to 96% using the Decision Tree (DT) classifier. The effectiveness of the measurement system is demonstrated in a real multi-resident scenario where two older people are monitored during their daily life. The collected data are processed, obtaining the AL and habits of the older people to assess their behavior.

Improving patient selection for use of consumer grade physical activity monitors in the hospital

BACKGROUND

Bedrest is toxic for inpatients and consumer grade physical activity monitors offer an economical solution to monitor patient ambulation. But these devices may not be accurate in debilitated hospitalized patients who frequently ambulate very slowly.

OBJECTIVE

To determine whether measures of physical capacity can help identify inpatients for whom wearable physical activity monitors may accurately measure step count.

METHODS

Prospective observational study of 54 adult inpatients with acute neurological diagnoses. Patients were assessed using 2 physical capacity assessments (Activity Measure for Post-Acute Care Inpatient Mobility Short Form [AM-PAC IMSF] and Katz Activities of Daily Living [ADL] scale). They also completed a 2-minute walk test (2MWT) wearing a consumer grade physical activity monitor.

RESULTS

The wearable activity monitor recorded steps (initiated) in 33 (61%) of the inpatients, and for 94% of inpatients with gait speeds >0.43 m/s. Physical capacity assessments correlated well with gait speed, AM-PAC IMSF r = 0.7, and Katz ADL r = 0.6, p < 0.05. When the physical activity monitor initiated, the mean absolute percent error (SD) comparing device calculated steps to observed steps, was 10% (13). AM-PAC IMSF (T-score >45) and Katz ADL (>5) cutoff scores identified inpatients for whom physical activity monitors initiated with a sensitivity of 94 and 91%, respectively.

CONCLUSIONS

Physical capacity assessments, such as AM-PAC, and Katz ADL, may be a useful and feasible screening strategy to help identify inpatients where wearable physical activity monitors can measure their mobility.

Wrist accelerometry for monitoring dementia agitation behaviour in clinical settings: A scoping review

Agitated behaviour among elderly people with dementia is a challenge in clinical management. Wrist accelerometry could be a versatile tool for making objective, quantitative, and long-term assessments. The objective of this review was to summarise the clinical application of wrist accelerometry to agitation assessments and ways of analysing the data. Two authors independently searched the electronic databases CINAHL, PubMed, PsycInfo, EMBASE, and Web of Science. Nine (n = 9) articles were eligible for a review. Our review found a significant association between the activity levels (frequency and entropy) measured by accelerometers and the benchmark instrument of agitated behaviour. However, the performance of wrist accelerometry in identifying the occurrence of agitation episodes was unsatisfactory. Elderly people with dementia have also been monitored in existing studies by investigating the at-risk time for their agitation episodes (daytime and evening). Consideration may be given in future studies on wrist accelerometry to unifying the parameters of interest and the cut-off and measurement periods, and to using a sampling window to standardise the protocol for assessing agitated behaviour through wrist accelerometry.

The relationships between step count and hospitalisation-associated outcomes in acutely hospitalised older adults - A systematic review

BACKGROUND AND PURPOSE

Although low ambulation among older adults has been linked to a broad range of adverse outcomes during and after acute hospitalisation, a systematic inquiry of the link between step count and these consequences is required. Therefore, the main purpose of this study is to systematically review the relationships between step count and hospitalisation-associated outcomes in acutely hospitalised older adults.

METHODS

The electronic databases MEDLINE, CINAHL, and Embase were searched for studies including older adults (above age 65) hospitalised in acute internal wards. The search included the following key terms: 'accelerometer', 'step count', 'hospital', 'internal ward', and 'older adults'. Step count measurement linked to short- and/or long-term outcome(s) during and/or after hospitalisation. All types of articles (except reviews) in English from 1990 to May 2020 were considered. The Newcastle-Ottawa Scale was used to assess the quality of the included observational studies. Randomised controlled trials (RCT) were evaluated using the PEDro scale. The review protocol was registered with PROSPERO International Prospective Register of Systematic Reviews. PRISMA guidelines were followed and a PRISMA checklist for reporting systematic reviews completed.

RESULTS

The search yielded 1340 articles, and of those, the inclusion criteria were met by 12 studies: eight prospective, three interventional (one randomised controlled trial), and one case-control. These studies included three major adverse hospitalisation outcomes associated with step count: functional decline, longer length of stay, and higher re-hospitalisation rate; however, the large heterogeneity in the studies' methodology makes meta-analysis impossible.

CONCLUSIONS

Daily step count during hospitalisation of older adults is negatively associated with adverse outcomes, but causation cannot be inferred due to inconsistent outcomes and various methodological limitations. More studies are needed to illuminate causal pathways and mechanisms underlying these relationships, especially to differentiate between the relative contribution of personal versus environmental factors.

Physical Activity Recognition Based on a Parallel Approach for an Ensemble of Machine Learning and Deep Learning Classifiers

Human activity recognition (HAR) by wearable sensor devices embedded in the Internet of things (IOT) can play a significant role in remote health monitoring and emergency notification to provide healthcare of higher standards. The purpose of this study is to investigate a human activity recognition method of accrued decision accuracy and speed of execution to be applicable in healthcare. This method classifies wearable sensor acceleration time series data of human movement using an efficient classifier combination of feature engineering-based and feature learning-based data representation. Leave-one-subject-out cross-validation of the method with data acquired from 44 subjects wearing a single waist-worn accelerometer on a smart textile, and engaged in a variety of 10 activities, yielded an average recognition rate of 90%, performing significantly better than individual classifiers. The method easily accommodates functional and computational parallelization to bring execution time significantly down.

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.

Measuring Activities of Daily Living in Stroke Patients with Motion Machine Learning Algorithms: A Pilot Study

Measuring activities of daily living (ADLs) using wearable technologies may offer higher precision and granularity than the current clinical assessments for patients after stroke. This study aimed to develop and determine the accuracy of detecting different ADLs using machine-learning (ML) algorithms and wearable sensors. Eleven post-stroke patients participated in this pilot study at an ADL Simulation Lab across two study visits. We collected blocks of repeated activity (“atomic” activity) performance data to train our ML algorithms during one visit. We evaluated our ML algorithms using independent semi-naturalistic activity data collected at a separate session. We tested Decision Tree, Random Forest, Support Vector Machine (SVM), and eXtreme Gradient Boosting (XGBoost) for model development. XGBoost was the best classification model. We achieved 82% accuracy based on ten ADL tasks. With a model including seven tasks, accuracy improved to 90%. ADL tasks included chopping food, vacuuming, sweeping, spreading jam or butter, folding laundry, eating, brushing teeth, taking off/putting on a shirt, wiping a cupboard, and buttoning a shirt. Results provide preliminary evidence that ADL functioning can be predicted with adequate accuracy using wearable sensors and ML. The use of external validation (independent training and testing data sets) and semi-naturalistic testing data is a major strength of the study and a step closer to the long-term goal of ADL monitoring in real-world settings. Further investigation is needed to improve the ADL prediction accuracy, increase the number of tasks monitored, and test the model outside of a laboratory setting.

The sit to stand to sit postural transition variability in the five time sit to stand test in older people with different fall histories

BACKGROUND

It has been proved that increased motion variability can be indicative of lack of stability. Despite the extensive literature on single sit to stand/stand to sit postural transitions analysis in older people, no studies to this date have assessed the sit to stand to sit (STSTS) transition variability in older adults.

RESEARCH QUESTION

To investigate the variability in STSTS transition during the five times sit to stand (FTSS) test in older people with different fall histories.

METHODS

Seventy-five older (80.5 ± 7.5) and twenty-five younger (27.7 ± 6.5) subjects participated in the study. The older participants were categorized into three groups of non-fallers, once-fallers, and multiple-fallers based on their fall histories. Subjects were fitted with an IMU at their lower backs and asked to fully stand up and then sit down again five times in a row. The angular rotation of the trunk in the sagittal plane was recorded. Using the DTW method, the first STSTS transition of each subject was compared to the last transition and the variability was measured. The correlation between STSTS variability and older participants' Berg balance scale (BBS) was investigated.

RESULTS

The STSTS variability results were significantly different in older fallers (multiple-fallers and once-fallers) compared to both younger participants and older non-fallers. The results yielded a sensitivity of 85.4 % and a specificity of 83.3 % in recognizing older fallers from older non-fallers and a sensitivity and specificity of 86.7 % and 85.7 % respectively in recognizing older multiple-fallers from other older participants. The STSTS variability was found to be significantly correlated with BBS.

SIGNIFICANCE

The findings demonstrated a strong indication of variability in the STSTS transition in older fallers and a significant correlation between STSTS variability and BBS. The results suggest that variability analysis of the STSTS transition has the potential to be used for fall risk analysis in older adults.

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.

Evening exercise is associated with lower odds of visual field progression in Chinese patients with primary open angle glaucoma

Background

Exercise is widely known to lower intraocular pressure and increase ocular blood flow, which may be beneficial for glaucoma management. However, there are few studies that have reported on the relationship between exercise and glaucoma progression. The aim of our study was to investigate the exercise habits of those with primary open angle glaucoma (POAG) and its association with the progression of visual field (VF) loss.

Methods

Daily physical activity (PA) was monitored by an accelerometer (ActiGraph wGT3x-BT) which patients wore for more than 10 h of being awake on their right wrists for 1 week.

Results

Seventy-one non-progressive and 27 progressive patients were enrolled in the study. 24-h moderate to vigorous physical activity (MVPA) exercise showed that POAG patients had similar variation trends consisting of 3 wave peaks and 2 wave hollows. Minutes spent in MVPA was 19.89 ± 15.81 and 21.62 ± 15.10 during 07:00–09:00 h (p = 0.204), 15.40 ± 14.49 and 15.67 ± 12.43 during 15:00–17:00 h (p = 0.822) and 17.26 ± 21.11 and 11.42 ± 11.58 during 18:00–20:00 h (p = 0.001) in the non-progressive and progressive group, respectively. Univariate analysis indicated that 10 min of MVPA (18:00–20:00 h) [odds ratio, OR (95% CI) = 0.82 (0.73, 0.92)], average mean arterial pressure [OR (95% CI) = 0.96 (0.94, 0.98)], age [OR (95% CI) = 1.06 (1.03, 1.08)], male [OR (95% CI) = 0.67 (0.48, 0.96)], spherical equivalent [OR (95% CI) = 1.14 (1.07, 1.22)] and IOP-lowering medications [OR (95% CI) = 1.54 (1.16, 2.05)] were significantly correlated with having progressive VF damage. Multivariable analysis showed that 10 min of MVPA (18:00–20:00 h) [OR (95% CI) = 0.85 (0.75, 0.97)] was associated with progressive VF loss even after adjusting for other risk factors.

Conclusions

Evening exercise may lower the odds of VF progression, suggesting that exercise habits possibly play an important role in glaucoma progression.

Commercial Postural Devices: A Review

Wearables are devices worn on the human body and are able to measure various health parameters, such as physical activity, energy expenditure and gait. With the advancement of technology, the general population are now spending more hours craning our necks and slouching over smartphones, tablets and computers, et cetera. Bodily posture is representative of physical and mental health. Poor posture can lead to spinal complications and the same can be said vice versa. As the standard of living increases, there is an increase in consumerism and the expectation to maintain such a lifestyle even in the aging population. Therefore, many are able to afford small luxuries in life, such as a piece of technology that could potentially improve their health in the long run. Wearable technology is a promising alternative to laboratory systems for movement and posture analysis. This article reviews commercial wearable devices with a focus on postural analysis. The clinical applicability of posture wearables, particularly in preventing, monitoring and treating spinal and musculoskeletal conditions, along with other purposes in healthcare, will be discussed.

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.

StraightenUp+: Monitoring of Posture during Daily Activities for Older Persons Using Wearable Sensors

Monitoring the posture of older persons using portable sensors while they carry out daily activities can facilitate the process of generating indicators with which to evaluate their health and quality of life. The majority of current research into such sensors focuses primarily on their functionality and accuracy, and minimal effort is dedicated to understanding the experience of older persons who interact with the devices. This study proposes a wearable device to identify the bodily postures of older persons, while also looking into the perceptions of the users. For the purposes of this study, thirty independent and semi-independent older persons undertook eight different types of physical activity, including: walking, raising arms, lowering arms, leaning forward, sitting, sitting upright, transitioning from standing to sitting, and transitioning from sitting to standing. The data was classified offline, achieving an accuracy of 93.5%, while overall device user perception was positive. Participants rated the usability of the device, in addition to their overall user experience, highly.

Accelerometric Trunk Sensors to Detect Changes of Body Positions in Immobile Patients

Mobilization, verticalization and position change are mandatory for severely affected neurological patients in early neurorehabilitation in order to improve neurological status and prevent complications. However, with the exception of hospitals and rehabilitation facilities, this activity is not usually monitored and so far the automated monitoring of position changes in immobile patients has not been investigated. Therefore, we investigated whether accelerometers on the upper trunk could reliably detect body position changes in immobile patients. Thirty immobile patients in early neurorehabilitation (Barthel Index ≤ 30) were enrolled. Two tri-axial accelerometers were placed on the upper trunk and on the thigh. Information on the position and position changes of the subject were derived from accelerometer data and compared to standard written documentation in the hospital over 24 h. Frequency and duration of different body positions (supine, sidelying, sitting) were measured. Data are presented as mean ± SEM. Groups were compared using one-way ANOVA or Kruskal-Wallis-test. Differences were considered significant if p < 0.05. Trunk sensors detected 100% and thigh sensors 66% of position changes (p = 0.0004) compared to standard care documentation. Furthermore, trunk recording also detected additional spontaneous body position changes that were not documented in standard care (81.8 ± 4.4% of all position changes were documented in standard care documentation) (p < 0.0001). We found that accelerometric trunk sensors are suitable for recording position changes and mobilization of severely affected patients. Our findings suggest that using accelerometers for care documentation is useful for monitoring position changes and mobilization frequencies in and outside of hospital for severely affected neurological patients. Accelerometric sensors may be valuable in monitoring continuation of care plans after intensive neurorehabilitation.

A study of measurement properties of the Life-Space Assessment questionnaire in older adults with chronic obstructive pulmonary disease

OBJECTIVE

To test the measurement properties (reliability, interpretability, and validity) of the Life-Space Assessment questionnaire for older adults with chronic obstructive pulmonary disease.

DESIGN

Clinimetric study.

SETTING

Pneumology service, ambulatory care, São Paulo, SP, Brazil.

PARTICIPANTS

Consecutive sample of older adults ( n = 62; 38 (61%) men, 24 (39%) women) with chronic obstructive pulmonary disease.

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURES

Life-Space Assessment questionnaire assesses five space levels visited by the older adult in four weeks prior to the assessment. We tested the following measurement properties of this questionnaire: reliability (reproducibility assessed by a type-2,1 intraclass correlation coefficient (ICC_2,1); internal consistency assessed by the Cronbach's alpha; measurement error by determining the standard error of measurement (SEM)), interpretability (minimum detectable change with 90% confidence (MDC₉₀); ceiling and floor effects by calculating the proportion of participants who achieved the minimum and maximum scores), and validity by Pearson's correlation test between the Life-Space Assessment questionnaire scores and number of daily steps assessed by accelerometry.

RESULTS

Reproducibility (ICC_2,1) was 0.90 (95% confidence interval (CI): 0.84-0.94), and internal consistency (Cronbach's α) was 0.80 (range = 0.76-0.80 for each item deleted). SEM was 3.65 points (3%), the MDC₉₀ was 0.20 points, and we observed no ceiling (2%) or floor (6%) effects. We observed an association between the score of the Life-Space Assessment questionnaire and daily steps ( r = 0.43; P = 0.01).

CONCLUSION

Life-Space Assessment questionnaire shows adequate measurement properties for the assessment of life-space mobility in older adults with chronic obstructive pulmonary disease.

A systematic literature review of reviews on techniques for physical activity measurement in adults: a DEDIPAC study

The links between increased participation in Physical Activity (PA) and improvements in health are well established. As this body of evidence has grown, so too has the search for measures of PA with high levels of methodological effectiveness (i.e. validity, reliability and responsiveness to change). The aim of this “review of reviews” was to provide a comprehensive overview of the methodological effectiveness of currently employed measures of PA, to aid researchers in their selection of an appropriate tool. A total of 63 review articles were included in this review, and the original articles cited by these reviews were included in order to extract detailed information on methodological effectiveness.

Self-report measures of PA have been most frequently examined for methodological effectiveness, with highly variable findings identified across a broad range of behaviours. The evidence-base for the methodological effectiveness of objective monitors, particularly accelerometers/activity monitors, is increasing, with lower levels of variability observed for validity and reliability when compared to subjective measures. Unfortunately, responsiveness to change across all measures and behaviours remains under-researched, with limited information available.

Other criteria beyond methodological effectiveness often influence tool selection, including cost and feasibility. However, researchers must be aware of the methodological effectiveness of any measure selected for use when examining PA. Although no “perfect” tool for the examination of PA in adults exists, it is suggested that researchers aim to incorporate appropriate objective measures, specific to the behaviours of interests, when examining PA in free-living environments.

Stroke Prevention Rehabilitation Intervention Trial of Exercise (SPRITE) - a randomised feasibility study

BACKGROUND

The value of cardiac rehabilitation (CR) after a transient ischaemic attack (TIA) or minor stroke is untested despite these conditions sharing similar pathology and risk factors to coronary heart disease. We aimed to evaluate the feasibility of conducting a trial of an adapted home-based CR programme, 'The Healthy Brain Rehabilitation Manual', for patients following a TIA/minor stroke, participants' views on the intervention and, to identify the behaviour change techniques (BCTs) used.

METHODS

Clinicians were asked to identify patients attending the Ulster Hospital, Belfast within 4 weeks of a first TIA or minor stroke. Those who agreed to participate underwent assessments of physical fitness, cardiovascular risk, quality of life and mental health, before random allocation to: Group (1) standard/usual care; (2) rehabilitation manual or (3) manual plus pedometer. All participants received telephone support at 1 and 4 weeks, reassessment at 6 weeks and an invitation to a focus group exploring views regarding the study. Two trained review authors independently assessed the manual to identify the BCTs used.

RESULTS

Twenty-eight patients were invited to participate, with 15 (10 men, 5 women; 9 TIA, 6 minor stroke; mean age 69 years) consenting and completing the study. Mean time to enrolment from the TIA/stroke was 20.5 days. Participants completed all assessment measures except VO2max testing, which all declined. The manual and telephone contact were viewed positively, as credible sources of advice. Pedometers were valued highly, particularly for goal-setting. Overall, 36 individual BCTs were used, the commonest being centred around setting goals and planning as well as social support.

CONCLUSION

Recruitment and retention rates suggest that a trial to evaluate the effectiveness of a novel home-based CR programme, implemented within 4 weeks of a first TIA/minor stroke is feasible. The commonest BCTs used within the manual revolve around goals, planning and social support, in keeping with UK national guidelines. The findings from this feasibility work have been used to further refine the next stage of the intervention's development, a pilot study.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT02712385 . This study was registered prospectively on 18/03/2016.

Systemic effects of chronic obstructive pulmonary disease in young-old adults' life-space mobility

PURPOSE

The objective was to assess whether dyspnea, peripheral muscle strength and the level of physical activity are correlated with life-space mobility of older adults with COPD.

PATIENTS AND METHODS

Sixty patients over 60 years of age (40 in the COPD group and 20 in the control group) were included. All patients were evaluated for lung function (spirometry), life-space mobility (University of Alabama at Birmingham Study of Aging Life-Space Assessment), dyspnea severity (Modified Dyspnea Index), peripheral muscle strength (handgrip dynamometer), level of physical activity and number of daily steps (accelerometry). Groups were compared using unpaired t-test. Pearson's correlation was used to test the association between variables.

RESULTS

Life-space mobility (60.41±16.93 vs 71.07±16.28 points), dyspnea (8 [7-9] vs 11 [10-11] points), peripheral muscle strength (75.16±14.89 vs 75.50±15.13 mmHg), number of daily steps (4,865.4±2,193.3 vs 6,146.8±2,376.4 steps), and time spent in moderate to vigorous activity (197.27±146.47 vs 280.05±168.95 minutes) were lower among COPD group compared to control group (p<0.05). The difference was associated with the lower mobility of COPD group in the neighborhood.

CONCLUSION

Life-space mobility is decreased in young-old adults with COPD, especially at the neighborhood level. This impairment is associated to higher dyspnea, peripheral muscle weakness and the reduced level of physical activity.

Physical Activity and Depressive Mood in the Daily Life of Older Adults

Abstract. Empirical evidence suggests that physical activity is related to less depressive moods. However, little is known about this association in the everyday life of older adults, limiting the ecological validity of prior findings. This study examined within-person associations between physical activity and depressive mood in older adults across 7 days. Moreover, the study tested the extent to which need-fulfillment can explain this association. The sample consisted of 68 adults aged 65 to 93 years. Physical activity was assessed objectively with accelerometers, whereas need-fulfillment and depressive mood were assessed at the end of each day using self-reports. Results from multilevel analysis suggest that daily physical activity was negatively related to daily depressive mood within persons. Although need-fulfillment did not explain the association between physical activity and depressive mood, it was a statistically significant predictor of daily depressive mood and even attenuated the effect of physical activity on depressive mood to nonsignificance.

Evaluating Walking Intensity with Hip-Worn Accelerometers in Elders

PURPOSE

Accelerometer activity counts are used to objectively categorize physical activity levels. We examined the association between accelerometer activity counts and metabolic effort in older adults.

METHODS

Forty-five older adults (76.3 ± 5.1 yr) completed a 400-m walk at both a usual and a rapid pace. A portable metabolic unit measured pulmonary gas exchange, whereas a hip-worn accelerometer measured activity counts. Participants were categorized as either a "slow walker" or a "fast walker" based on the threshold of 1.0 m·s during usual-pace walking.

RESULTS

Activity counts during rapid (r = 0.62, P < 0.01) but not usual-pace (r = 0.24, P = 0.11) walking were significantly associated with METs. Slow walkers attained only half the activity counts of fast walkers during each walk condition (P < 0.01), while at the same time achieving between 82% and 90% of their MET level.

CONCLUSION

Accelerometers may misclassify the activity level of functionally impaired older adults with slow walking speed.

Validity and reliability of accelerometry in identification of lying, sitting, standing or purposeful activity in adult hospital inpatients recovering from acute or critical illness: a systematic review

Objective:

To investigate the validity and reliability of accelerometers to detect lying, sitting and standing postures or purposeful activity in hospitalized adults recovering from acute or critical illness.

Data sources:

CINAHL, MEDLINE, EMBASE, AMED, Cochrane Library, PEDro, PsycINFO and SPORTDiscuss were searched from inception to June 2017. Professional networks and reference lists of relevant articles were also searched. The main selection criteria were hospitalized adults with acute or critical illness and studies investigating the validity or reliability of accelerometers to identify body position or purposeful activity.

Review methods:

Two authors individually assessed study eligibility and independently undertook methodological quality assessment and data extraction from selected articles. A narrative synthesis of the data was undertaken.

Results:

Fifteen studies, collectively enrolling 385 hospitalized participants, were identified. Populations included stroke, the elderly, acute exacerbation of chronic respiratory disease, abdominal surgery and those recovering from critical illness. Correlations of r = 0.36 to 0.98 and levels of agreement of κ = 0.28 to 0.98 were reported for identification of lying, sitting or standing postures. Correlations of r = 0.4 to 0.8 with general activity were found, with r = 0.94 and 0.96 reported for step count. The reliability of accelerometry measurement was investigated in one study evaluating step count quantification (intraclass correlation coefficient (ICC) = 0.99, 95% confidence interval (CI) = 0.99–1.00).

Conclusion:

The validity of accelerometers to determine lying, sitting and standing postures or quantify purposeful activity within hospitalized acute or critically ill populations is variable. The reliability of accelerometry measurement within this setting remains largely unexplored.

Activity Recognition in Individuals Walking With Assistive Devices: The Benefits of Device-Specific Models

BACKGROUND

Wearable sensors gather data that machine-learning models can convert into an identification of physical activities, a clinically relevant outcome measure. However, when individuals with disabilities upgrade to a new walking assistive device, their gait patterns can change, which could affect the accuracy of activity recognition.

OBJECTIVE

The objective of this study was to assess whether we need to train an activity recognition model with labeled data from activities performed with the new assistive device, rather than data from the original device or from healthy individuals.

METHODS

Data were collected from 11 healthy controls as well as from 11 age-matched individuals with disabilities who used a standard stance control knee-ankle-foot orthosis (KAFO), and then a computer-controlled adaptive KAFO (Ottobock C-Brace). All subjects performed a structured set of functional activities while wearing an accelerometer on their waist, and random forest classifiers were used as activity classification models. We examined both global models, which are trained on other subjects (healthy or disabled individuals), and personal models, which are trained and tested on the same subject.

RESULTS

Median accuracies of global and personal models trained with data from the new KAFO were significantly higher (61% and 76%, respectively) than those of models that use data from the original KAFO (55% and 66%, respectively) (Wilcoxon signed-rank test, P=.006 and P=.01). These models also massively outperformed a global model trained on healthy subjects, which only achieved a median accuracy of 53%. Device-specific models conferred a major advantage for activity recognition.

CONCLUSIONS

Our results suggest that when patients use a new assistive device, labeled data from activities performed with the specific device are needed for maximal precision activity recognition. Personal device-specific models yield the highest accuracy in such scenarios, whereas models trained on healthy individuals perform poorly and should not be used in patient populations.

Accelerometer-Measured Daily Activity in Heart Failure With Preserved Ejection Fraction: Clinical Correlates and Association With Standard Heart Failure Severity Indices

BACKGROUND

Daily physical activity assessed by accelerometers represents a novel method to assess the impact of interventions on heart failure (HF) patients' functional status. We hypothesized that daily activity varies by patient characteristics and correlates with established measures of HF severity in HF with preserved ejection fraction.

METHODS AND RESULTS

In this ancillary study of the NEAT-HFpEF trial (Nitrate's Effects on Activity Tolerance in HF With Preserved Ejection Fraction), average daily accelerometer units (ADAU) and hours active per day were assessed during a 14-day period before starting isosorbide mononitrate or placebo (n=110). Baseline ADAU was negatively associated with age, female sex, height, and body mass index, and these variables accounted for 28% of the variability in ADAU (P<0.007 for all). Adjusting for these factors, patients with lower ADAU were more likely to have had an HF hospitalization, orthopnea, diabetes mellitus and anemia, be treated with β-blockers, have higher ejection fraction, relative wall thickness and left atrial volume, and worse New York Heart Association class, HF-specific quality of life scores, 6-minute walk distance, and NT-proBNP (N-terminal pro-B-type natriuretic peptide; P<0.05 for all). Associations between hours active per day and clinical characteristics were similar. Relative to baseline, there were no significant associations between changes in ADAU or hours active per day and changes in standard functional assessments (New York Heart Association, quality of life, 6-minute walk distance, and NT-proBNP) with isosorbide mononitrate.

CONCLUSIONS

Daily activity is a measure of HF-related and global functional status in HF with preserved ejection fraction. As compared with intermittently assessed standard HF assessments, change in daily activity may provide unique information about the impact of HF interventions on functional status.

CLINICAL TRIAL REGISTRATION

URL: https://www.clinicaltrials.gov/. Unique identifier: NCT02053493.

Activity recognition in patients with lower limb impairments: do we need training data from each patient?

Machine learning allows detecting specific physical activities using data from wearable sensors. Such a quantification of patient mobility over time promises to accurately inform clinical decisions for physical rehabilitation. There are two strategies of setting up the machine learning problem: detect one patient's activities using data from the same patient (personal model) or detect their activities using data from other patients (global model), and we currently do not know if personal models are necessary. Here we consider the problem of detecting physical activities from a waist-worn accelerometer in patients who use a knee-ankle-foot orthosis (KAFO) to walk. We show that while a model based on healthy subjects has low accuracy, the global model performs as well as the personal model. This is encouraging because it suggests that condition-specific activity recognition algorithms are sufficient and that no data from individual patients is necessary.

Application of data fusion techniques and technologies for wearable health monitoring

Technological advances in sensors and communications have enabled discrete integration into everyday objects, both in the home and about the person. Information gathered by monitoring physiological, behavioural, and social aspects of our lives, can be used to achieve a positive impact on quality of life, health, and well-being. Wearable sensors are at the cusp of becoming truly pervasive, and could be woven into the clothes and accessories that we wear such that they become ubiquitous and transparent. To interpret the complex multidimensional information provided by these sensors, data fusion techniques are employed to provide a meaningful representation of the sensor outputs. This paper is intended to provide a short overview of data fusion techniques and algorithms that can be used to interpret wearable sensor data in the context of health monitoring applications. The application of these techniques are then described in the context of healthcare including activity and ambulatory monitoring, gait analysis, fall detection, and biometric monitoring. A snap-shot of current commercially available sensors is also provided, focusing on their sensing capability, and a commentary on the gaps that need to be bridged to bring research to market.

Wrist-worn triaxial accelerometry predicts the energy expenditure of non-vigorous daily physical activities

OBJECTIVES

Triaxial accelerometry is commonly used to estimate oxygen uptake (VO₂) and energy expenditure in health and fitness studies. We tested the correlation of a triaxial accelerometer in terms of a summation of vector magnitudes with gravity subtracted (SVMgs) and measured VO₂ for different daily physical activities.

DESIGN

Original research, cross-sectional.

METHODS

Twenty volunteers wore a triaxial accelerometer on both wrists while performing 12 assigned daily physical activities for 6min for each activity. The VO₂ was determined by indirect calorimetry using a portable metabolic measurement system. The last 3min of each activity was assumed to represent steady-state. The VO₂ measured during these periods was averaged and converted into metabolic equivalents (METs).

RESULTS

The range of VO₂ for all activities was 0.18-3.2L/min (0.8-12.2 METs). Significant differences in SVMgs existed between accelerometer placements on the dominant (120.9±8.7gmin) versus non-dominant hand (99.9±6.8gmin; P=0.016) for the lowest levels of physical activity defined as <1.5 METs. Piecewise linear regression model using 6 METs as the transition point showed similar significant correlations for the non-dominant wrist (r²=0.85; P<0.001) and the dominant wrist (r²=0.86; P<0.001). Using the non-dominant wrist below 6 METs, the slope of the relationship between SVMgs and METs was 105.3±4.3 (95% CI 96.9 to 113.7) indicating an increase in SVMgs of approximately 100 units for every MET increase in oxygen uptake.

CONCLUSIONS

Wrist-worn triaxial accelerometry reliably predicted energy expenditure during common physical activities <6 METs. More consistent correlations were found when the accelerometer was worn on the non-dominant wrist rather than the dominant wrist.

Promoting Activity in Geriatric Rehabilitation: A Randomized Controlled Trial of Accelerometry

Background

Low activity levels in inpatient rehabilitation are associated with adverse outcomes. The study aimed to test whether activity levels can be increased by the provision of monitored activity data to patients and clinicians in the context of explicit goal setting.

Methods

A randomized controlled trial in three sites in Australia included 255 inpatients aged 60 and older who had a rehabilitation goal to become ambulant. The primary outcome was patients’ walking time measured by accelerometers during the rehabilitation admission. Walking times from accelerometry were made available daily to treating therapists and intervention participants to motivate patients to improve incidental activity levels and reach set goals. For the control group, ‘usual care’ was followed, including the setting of mobility goals; however, for this group, neither staff nor patients received data on walking times to aid the setting of daily walking time targets.

Results

The median daily walking time in the intervention group increased from 10.3 minutes at baseline to 32.1 minutes at day 28, compared with an increase from 9.5 to 26.5 minutes per day in the control group. Subjects in the intervention group had significantly higher non-therapy walking time by about 7 minutes [mean (95% CI): 24.6 (21.7, 27.4)] compared to those in the control group [mean(95% CI): 17.3 (14.4, 20.3)] (p = 0.001).

Conclusions

Daily feedback to patients and therapists using an accelerometer increased walking times during rehabilitation admissions. The results of this study suggest objective monitoring of activity levels could provide clinicians with information on clinically important, mobility-related activities to assist goal setting.

Trial Registration

Australian New Zealand Clinical Trials Registry ACTRN12611000034932 http://www.ANZCTR.org.au/

Human Activity Recognition in AAL Environments Using Random Projections

Automatic human activity recognition systems aim to capture the state of the user and its environment by exploiting heterogeneous sensors attached to the subject's body and permit continuous monitoring of numerous physiological signals reflecting the state of human actions. Successful identification of human activities can be immensely useful in healthcare applications for Ambient Assisted Living (AAL), for automatic and intelligent activity monitoring systems developed for elderly and disabled people. In this paper, we propose the method for activity recognition and subject identification based on random projections from high-dimensional feature space to low-dimensional projection space, where the classes are separated using the Jaccard distance between probability density functions of projected data. Two HAR domain tasks are considered: activity identification and subject identification. The experimental results using the proposed method with Human Activity Dataset (HAD) data are presented.

Evaluation of a smartphone human activity recognition application with able-bodied and stroke participants

Background

Mobile health monitoring using wearable sensors is a growing area of interest. As the world’s population ages and locomotor capabilities decrease, the ability to report on a person’s mobility activities outside a hospital setting becomes a valuable tool for clinical decision-making and evaluating healthcare interventions. Smartphones are omnipresent in society and offer convenient and suitable sensors for mobility monitoring applications. To enhance our understanding of human activity recognition (HAR) system performance for able-bodied and populations with gait deviations, this research evaluated a custom smartphone-based HAR classifier on fifteen able-bodied participants and fifteen participants who suffered a stroke.

Methods

Participants performed a consecutive series of mobility tasks and daily living activities while wearing a BlackBerry Z10 smartphone on their waist to collect accelerometer and gyroscope data. Five features were derived from the sensor data and used to classify participant activities (decision tree). Sensitivity, specificity and F-scores were calculated to evaluate HAR classifier performance.

Results

The classifier performed well for both populations when differentiating mobile from immobile states (F-score > 94 %). As activity recognition complexity increased, HAR system sensitivity and specificity decreased for the stroke population, particularly when using information derived from participant posture to make classification decisions.

Conclusions

Human activity recognition using a smartphone based system can be accomplished for both able-bodied and stroke populations; however, an increase in activity classification complexity leads to a decrease in HAR performance with a stroke population. The study results can be used to guide smartphone HAR system development for populations with differing movement characteristics.

Isosorbide Mononitrate in Heart Failure with Preserved Ejection Fraction

BACKGROUND

Nitrates are commonly prescribed to enhance activity tolerance in patients with heart failure and a preserved ejection fraction. We compared the effect of isosorbide mononitrate or placebo on daily activity in such patients.

METHODS

In this multicenter, double-blind, crossover study, 110 patients with heart failure and a preserved ejection fraction were randomly assigned to a 6-week dose-escalation regimen of isosorbide mononitrate (from 30 mg to 60 mg to 120 mg once daily) or placebo, with subsequent crossover to the other group for 6 weeks. The primary end point was the daily activity level, quantified as the average daily accelerometer units during the 120-mg phase, as assessed by patient-worn accelerometers. Secondary end points included hours of activity per day during the 120-mg phase, daily accelerometer units during all three dose regimens, quality-of-life scores, 6-minute walk distance, and levels of N-terminal pro-brain natriuretic peptide (NT-proBNP).

RESULTS

In the group receiving the 120-mg dose of isosorbide mononitrate, as compared with the placebo group, there was a nonsignificant trend toward lower daily activity (-381 accelerometer units; 95% confidence interval [CI], -780 to 17; P=0.06) and a significant decrease in hours of activity per day (-0.30 hours; 95% CI, -0.55 to -0.05; P=0.02). During all dose regimens, activity in the isosorbide mononitrate group was lower than that in the placebo group (-439 accelerometer units; 95% CI, -792 to -86; P=0.02). Activity levels decreased progressively and significantly with increased doses of isosorbide mononitrate (but not placebo). There were no significant between-group differences in the 6-minute walk distance, quality-of-life scores, or NT-proBNP levels.

CONCLUSIONS

Patients with heart failure and a preserved ejection fraction who received isosorbide mononitrate were less active and did not have better quality of life or submaximal exercise capacity than did patients who received placebo. (Funded by the National Heart, Lung, and Blood Institute; ClinicalTrials.gov number, NCT02053493.).

Recovery Potential After Acute Stroke

In acute stroke, the major factor for recovery is the early use of thrombolysis aimed at arterial recanalization and reperfusion of ischemic brain tissue. Subsequently, neurorehabilitative training critically improves clinical recovery due to augmention of postlesional plasticity. Neuroimaging and electrophysiology studies have revealed that the location and volume of the stroke lesion, the affection of nerve fiber tracts, as well as functional and structural changes in the perilesional tissue and in large-scale bihemispheric networks are relevant biomarkers of post-stroke recovery. However, associated disorders, such as mood disorders, epilepsy, and neurodegenerative diseases, may induce secondary cerebral changes or aggravate the functional deficits and, thereby, compromise the potential for recovery.

Wrist Actigraphy: A Simple Way to Record Motor Activity in Elderly Patients with Dementia and Apathy or Aberrant Motor Behavior

INTRODUCTION

In dementia, behavioral psychological symptoms are frequent and variable.

OBJECTIVE

To assess the value of wrist actigraphy as a measure of disorder in motor behavior especially apathy, aberrant motor behavior, agitation and anxiety.

METHODS

Cross sectional observational study of consecutive patients older than 75 years admitted to an intermediate care unit of a geriatric hospital ward during a two-year period. Psycho behavioral symptoms and cognitive status were assessed using the NPI scale and MMSE and diagnosis of dementia was done using DSMIV criteria. A wrist actigraph was worn for 10 days to record motor activity, sleep time and number of periods of sleep.

RESULTS

183 patients were included. Among patients with dementia, a significant decrease in motor activity was recorded in those with apathy from 9h to 12h and 18h to 21h (p <0.05) and in those with anxiety from 21h to 24h (p <0.05). Aberrant motor behavior in dementia was associated with a significant increase in motor activity from 21h to 24h (p <0.01). Agitation was not associated with a significant differences in motor activity.

CONCLUSIONS

Wrist actigraphy can be used to record motor activity in elderly patients with dementia especially in those with apathy and aberrant motor behavior.

Feature selection for wearable smartphone-based human activity recognition with able bodied, elderly, and stroke patients

Human activity recognition (HAR), using wearable sensors, is a growing area with the potential to provide valuable information on patient mobility to rehabilitation specialists. Smartphones with accelerometer and gyroscope sensors are a convenient, minimally invasive, and low cost approach for mobility monitoring. HAR systems typically pre-process raw signals, segment the signals, and then extract features to be used in a classifier. Feature selection is a crucial step in the process to reduce potentially large data dimensionality and provide viable parameters to enable activity classification. Most HAR systems are customized to an individual research group, including a unique data set, classes, algorithms, and signal features. These data sets are obtained predominantly from able-bodied participants. In this paper, smartphone accelerometer and gyroscope sensor data were collected from populations that can benefit from human activity recognition: able-bodied, elderly, and stroke patients. Data from a consecutive sequence of 41 mobility tasks (18 different tasks) were collected for a total of 44 participants. Seventy-six signal features were calculated and subsets of these features were selected using three filter-based, classifier-independent, feature selection methods (Relief-F, Correlation-based Feature Selection, Fast Correlation Based Filter). The feature subsets were then evaluated using three generic classifiers (Naïve Bayes, Support Vector Machine, j48 Decision Tree). Common features were identified for all three populations, although the stroke population subset had some differences from both able-bodied and elderly sets. Evaluation with the three classifiers showed that the feature subsets produced similar or better accuracies than classification with the entire feature set. Therefore, since these feature subsets are classifier-independent, they should be useful for developing and improving HAR systems across and within populations.

Geriatric syndromes and functional status in NSHAP: rationale, measurement, and preliminary findings

INTRODUCTION

The geriatric functional measures and syndromes collected 5 years apart in Waves 1 and 2 of the National Social Life, Health, and Aging Project (NSHAP) data set included: difficulty with activities of daily living and instrumental activities of daily living, the timed up and go, a 3-m timed walk, repeated chair stands, self-reported physical activity, accelerometry-assessed (in)activity, falls, fractures, and frailty. The purpose of this paper was to describe the data collection methods and report preliminary population estimates for each measures.

METHOD

Frequencies, means, or medians were estimated for each measure stratified by age and gender, using the age-eligible samples in Wave 1 (n = 3,005) and Wave 2 (n = 3,196). An adapted phenotypic frailty scale was constructed in the sample common to both waves (n = 2,261). Changes over 5 years were reported for four measures common to both waves.

RESULTS

The functional measures worsened with age (p < .001). The syndromes were more prevalent with age except "all fractures" (p value range < .001-.03). Functional measures were worse among females than males except chair stand performance and the accelerometry-assessed (in)activity measures (p value range < .001-.01). The syndromes were more common among females than males except Wave 2 falls and Wave 2 hip fractures (p value range < .001-.03). Changes from Wave 1 to 2 revealed 11.5%-25.2% of individuals reported better health and 21.3%-44.7% reported worse health.

DISCUSSION

The NSHAP provides a comprehensive assessment of geriatric health. Our findings are consistent with the literature and support the construct of the study measures.

Accuracy, sensitivity and robustness of five different methods for the estimation of gait temporal parameters using a single inertial sensor mounted on the lower trunk

In the last decade, various methods for the estimation of gait events and temporal parameters from the acceleration signals of a single inertial measurement unit (IMU) mounted at waist level have been proposed. Despite the growing interest for such methodologies, a thorough comparative analysis of methods with regards to number of extra and missed events, accuracy and robustness to IMU location is still missing in the literature. The aim of this work was to fill this gap. Five methods have been tested on single IMU data acquired from fourteen healthy subjects walking while being recorded by a stereo-photogrammetric system and two force platforms. The sensitivity in detecting initial and final contacts varied between 81% and 100% across methods, whereas the positive predictive values ranged between 94% and 100%. For all tested methods, stride and step time estimates were obtained; three of the selected methods also allowed estimation of stance, swing and double support time. Results showed that the accuracy in estimating step and stride durations was acceptable for all methods. Conversely, a statistical difference was found in the error in estimating stance, swing and double support time, due to the larger errors in the final contact determination. Except for one method, the IMU positioning on the lower trunk did not represent a critical factor for the estimation of gait temporal parameters. Results obtained in this study may not be applicable to pathologic gait.

Wearable accelerometry-based technology capable of assessing functional activities in neurological populations in community settings: a systematic review

BACKGROUND

Integrating rehabilitation services through wearable systems has the potential to accurately assess the type, intensity, duration, and quality of movement necessary for procuring key outcome measures.

OBJECTIVES

This review aims to explore wearable accelerometry-based technology (ABT) capable of assessing mobility-related functional activities intended for rehabilitation purposes in community settings for neurological populations. In this review, we focus on the accuracy of ABT-based methods, types of outcome measures, and the implementation of ABT in non-clinical settings for rehabilitation purposes.

DATA SOURCES

Cochrane, PubMed, Web of Knowledge, EMBASE, and IEEE Xplore. The search strategy covered three main areas, namely wearable technology, rehabilitation, and setting.

STUDY SELECTION

Potentially relevant studies were categorized as systems either evaluating methods or outcome parameters.

METHODS

Methodological qualities of studies were assessed by two customized checklists, depending on their categorization and rated independently by three blinded reviewers.

RESULTS

Twelve studies involving ABT met the eligibility criteria, of which three studies were identified as having implemented ABT for rehabilitation purposes in non-clinical settings. From the twelve studies, seven studies achieved high methodological quality scores. These studies were not only capable of assessing the type, quantity, and quality measures of functional activities, but could also distinguish healthy from non-healthy subjects and/or address disease severity levels.

CONCLUSION

While many studies support ABT's potential for telerehabilitation, few actually utilized it to assess mobility-related functional activities outside laboratory settings. To generate more appropriate outcome measures, there is a clear need to translate research findings and novel methods into practice.

Can we use accelerometry to monitor balance exercise performance in older adults?

While home-based balance exercises are recommended to reduce the risk of falling and fractures in older adults, adherence to exercise remains suboptimal. The long-term objective of this research is to advance body-worn sensor techniques to measure at-home exercise performance and promote adherence. In this study, a method of distinguishing 5 types of walking using hip- and ankle-worn accelerometers was developed and evaluated in a target clinical population. A secondary objective was to evaluate the method's sensitivity to sensor placement. Eighteen community-dwelling, older females (≥50 years) with low bone mass wore triaxial accelerometers at the left hip and each ankle while performing 5 walking tasks at home: 4 walking balance exercises (figure 8, heel-toe, sidestep, backwards) and straight-line walking. Sensor data were separated into low (0.5-2 Hz) and high (2-10 Hz) frequency bands, and root-mean-square values (energy) were computed for each sensor, axis, and band. These 18 energy estimates were used as inputs to a neural network classifier with 5 outputs, corresponding to each task. Using a leave-one-out cross-validation protocol, the neural network correctly classified 82/90 test instances (91% accuracy). Compared to random selection accuracy of 20% (i.e., 1 in 5), the results indicated excellent separation between tasks. Reducing the sensor set to one hip and one ankle resulted in 6.7-8.9% reduction in accuracy. Our findings can be used in the development of tools used to deliver exercise performance metrics (e.g., % completed) or recognize walking and balance exercise activities using body-worn accelerometers.

Changes in spontaneous activity assessed by accelerometry correlate with extent of cerebral ischemia-reperfusion injury in the nonhuman primate

The use of accelerometry to monitor activity in human stroke patients has revealed strong correlations between objective activity measurements and subjective neurological findings. The goal of our study was to assess the applicability of accelerometry-based measurements in experimental animals undergoing surgically-induced cerebral ischemia. Using a nonhuman primate cortical stroke model, we demonstrate for the first time that monitoring locomotor activity prior to and following cerebrovascular ischemic injury using an accelerometer is feasible in adult male rhesus macaques and that the measured activity outcomes significantly correlate with severity of brain injury. The use of accelerometry as an unobtrusive, objective preclinical efficacy determinant could complement standard practices involving subjective neurological scoring and magnetic resonance imaging in nonhuman primates. Similar activity monitoring devices to those employed in this study are currently in use in human clinical studies, underscoring the feasibility of this approach for assessing the clinical potential of novel treatments for cerebral ischemia.

Monitoring human health behaviour in one's living environment: a technological review

The electronic monitoring of human health behaviour using computer techniques has been an active research area for the past few decades. A wide array of different approaches have been investigated using various technologies including inertial sensors, Global Positioning System, smart homes, Radio Frequency IDentification and others. It is only in recent years that research has turned towards a sensor fusion approach using several different technologies in single systems or devices. These systems allow for an increased volume of data to be collected and for activity data to be better used as measures of behaviour. This change may be due to decreasing hardware costs, smaller sensors, increased power efficiency or increases in portability. This paper is intended to act as a reference for the design of multi-sensor behaviour monitoring systems. The range of technologies that have been used in isolation for behaviour monitoring both in research and commercial devices are reviewed and discussed. Filtering, range, sensitivity, usability and other considerations of different technologies are discussed. A brief overview of commercially available activity monitors and their technology is also included.

In patients with neovascular age-related macular degeneration, physical activity may influence C-reactive protein levels

Purpose

Association of neovascular age-related macular degeneration (AMD) with C-reactive protein (CRP) was previously reported, indicating a relation to systemic low-grade inflammation. However, visual impairment limits physical activity, and physical activity modulates CRP levels. Here, we investigated the impact of physical activity on CRP levels in patients with neovascular AMD and control individuals.

Subjects and methods

We recruited participants from our outpatient AMD program, and control individuals from non-AMD patients, visitors, and department staff. After initial screening of 191 individuals, we included 98 patients with neovascular AMD and 77 controls. All were screened using digital fundus photography and optical coherence tomography, and interviewed about medical history and physical activity. Venous blood samples were obtained for high-sensitivity CRP.

Results

Physically active individuals had lower CRP than physically inactive individuals (P=0.003), and physical activity was associated with lower CRP in patients (P=0.038) and controls (P=0.031). Patients and controls did not differ in percentage physically active (P=0.807) or in overall CRP levels (P=0.394). The independent contribution of physical activity on CRP was confirmed in a multiple regression analysis (P=0.009), in which the presence of neovascular AMD did not contribute significantly (P=0.913).

Conclusion

Our findings suggest that elevated CRP levels in patients with neovascular AMD are at least partly explained by physical inactivity. Future studies of systemic inflammation among the visually impaired should include disease-related implications, such as the impact of physical activity.

Comparison of median frequency between traditional and functional sensor placements during activity monitoring

Long-term monitoring is of great clinical relevance. Accelerometers are often used to provide information about activities of daily living. The median frequency (f_m) of acceleration has recently been suggested as a powerful parameter for activity recognition. However, compliance issues arise when people need to integrate activity recognition sensors into their daily lives. More functional placements should provide higher levels of conformity, but may also affect the quality and generalizability of the signals. How f_m changes as a result of a more functional sensor placement remains unclear. This study investigates the agreement in f_m for a sensor placed on the back with one in the pocket across a range of daily activities. The translational and gravitational accelerations are also computed to determine if the accelerometer should be fused with additional sensors to improve agreement. Twelve subjects were tested over four tasks and only the "vertical" x-axis showed a moderate agreement (Intraclass Correlation Coefficient of 0.54) after correction for outliers. Generalizability across traditional and functional sensor locations might therefore be limited. Differentiation of the signal into a translational and gravitational component decreased the level of agreement further, suggesting that combined information streams are more robust to changing locations then singular data streams. Integrating multiple sensor modalities to obtain specific components is unlikely to improve agreement across sensor locations. More research is needed to explore measurement signals of more user friendly sensor configurations that will lead to a greater clinical acceptance of body worn sensor systems.

Aging, the central nervous system, and mobility

BACKGROUND

Mobility limitations are common and hazardous in community-dwelling older adults but are largely understudied, particularly regarding the role of the central nervous system (CNS). This has limited development of clearly defined pathophysiology, clinical terminology, and effective treatments. Understanding how changes in the CNS contribute to mobility limitations has the potential to inform future intervention studies.

METHODS

A conference series was launched at the 2012 conference of the Gerontological Society of America in collaboration with the National Institute on Aging and the University of Pittsburgh. The overarching goal of the conference series is to facilitate the translation of research results into interventions that improve mobility for older adults.

RESULTS

Evidence from basic, clinical, and epidemiological studies supports the CNS as an important contributor to mobility limitations in older adults without overt neurologic disease. Three main goals for future work that emerged were as follows: (a) develop models of mobility limitations in older adults that differentiate aging from disease-related processes and that fully integrate CNS with musculoskeletal contributors; (b) quantify the contribution of the CNS to mobility loss in older adults in the absence of overt neurologic diseases; (c) promote cross-disciplinary collaboration to generate new ideas and address current methodological issues and barriers, including real-world mobility measures and life-course approaches.

CONCLUSIONS

In addition to greater cross-disciplinary research, there is a need for new approaches to training clinicians and investigators, which integrate concepts and methodologies from individual disciplines, focus on emerging methodologies, and prepare investigators to assess complex, multisystem associations.