Activity Monitoring and Heart Rate Variability as Indicators of Fall Risk: Proof-of-Concept for Application of Wearable Sensors in the Acute Care Setting

Technological prospecting of patents related to monitoring accidents due to falls in hospitals

OBJECTIVES

to map the production of technologies aimed at monitoring falls in a hospital environment protected by registered patents.

METHODS

a technological prospecting of international patents, with a quantitative approach, with search carried out between February and March 2022 in the Derwent Innovations Index database with descriptors fall, hospital, monitoring.

RESULTS

212 patents were found, with the majority filed and published since 2010, by Tran B (9) and Cerner Innovation Inc (9), focused on health technology. Universities were responsible for 13% of deposits. There was a predominance of records from the United States (43.4%), China (21.7%) and Japan (12.3%), in addition to technological strategies classified as devices for the environment (80.7%) and for preventing falls (66.5%) as well as trend towards resources with multiple functionalities in the same technology.

CONCLUSIONS

the plurality of functions in the same device reflects the search for optimizing resources and the concern with comprehensive care.

Harnessing physical activity monitoring and digital biomarkers of frailty from pendant based wearables to predict chemotherapy resilience in veterans with cancer

This study evaluated the use of pendant-based wearables for monitoring digital biomarkers of frailty in predicting chemotherapy resilience among 27 veteran cancer patients (average age: 64.6 ± 13.4 years), undergoing bi-weekly chemotherapy. Immediately following their first day of chemotherapy cycle, participants wore a water-resistant pendant sensor for 14 days. This device tracked frailty markers like cadence (slowness), daily steps (inactivity), postural transitions (weakness), and metrics such as longest walk duration and energy expenditure (exhaustion). Participants were divided into resilient and non-resilient groups based on adverse events within 6 months post-chemotherapy, including dose reduction, treatment discontinuation, unplanned hospitalization, or death. A Chemotherapy-Resilience-Index (CRI) ranging from 0 to 1, where higher values indicate poorer resilience, was developed using regression analysis. It combined physical activity data with baseline Eastern Cooperative Oncology Group (ECOG) assessments. The protocol showed a 97% feasibility rate, with sensor metrics effectively differentiating between groups as early as day 6 post-therapy. The CRI, calculated using data up to day 6 and baseline ECOG, significantly distinguished resilient (CRI = 0.2 ± 0.27) from non-resilient (CRI = 0.7 ± 0.26) groups (p < 0.001, Cohen's d = 1.67). This confirms the potential of remote monitoring systems in tracking post-chemotherapy functional capacity changes and aiding early non-resilience detection, subject to validation in larger studies.

Advances in mobility aid use reporting: situational context and objective measurement improve understanding of daily aid use in older adults

BACKGROUND

Understanding mobility aid use has implications for falls risk reduction and aid prescription. However, aid use in daily life is understudied and more complex than revealed by commonly used yes/no self-reporting.

AIMS

To advance approaches for evaluating mobility aid use among older adults using a situational (context-driven) questionnaire and wearable sensors.

METHODS

Data from two cross-sectional observational studies of older adults were used: (1) 190 participants (86 ± 5 years) completed tests of standing, sit-to-stand, walking, grip strength, and self-reported fear of falling and (2) 20 participants (90 ± 4 years) wore two body-worn and one aid-mounted sensors continuously for seven days to objectively quantify aid use during walking. Situational and traditional binary reporting stratified participants into aid dependency levels (0-4) and aid-user groups, respectively. Physical performance and fear of falling were compared between aid users, and dependency levels and sensor-derived walking behaviors were compared to reported aid use.

RESULTS

Physical performance and fear of falling differed between aid-user groups (P < 0.05). Sensor-derived outputs revealed differences in walking behaviors and aid use when categorized by dependency level and walking bout length (P < 0.05). Walking bout frequency (rho(18) = - 0.47, P = 0.038) and aid use time (rho(13) = .72, P = 0.002) were associated with dependency level.

DISCUSSION

Comparisons of situational aid dependency revealed heterogeneity between aid users suggesting binary aid use reporting fails to identify individual differences in walking and aid use behaviors.

CONCLUSIONS

Enhanced subjective aid use reporting and objective measurements of walking and aid use may improve aid prescription and inform intervention to support safe and effective mobility in older adults.

Increased Parasympathetic Activity as a Fall Risk Factor Beyond Conventional Factors in Institutionalized Older Adults with Mild Cognitive Impairment

PURPOSE

This study aimed to investigate autonomic nervous function during the orthostatic challenge and its relationship with depression and fall, and to elucidate fall-associated factors, including autonomic function, executive function, and depression among institutionalized older adults with mild cognitive impairment (MCI).

METHODS

This study employed a descriptive cross-sectional design. Fall experiences in the current institutions were researched. Heart rate variability (HRV) during the orthostatic challenge was measured. Executive function was evaluated using the semantic verbal fluency test and clock drawing test. Depression was assessed using the Geriatric Depression Scale.

RESULTS

Of the 115 older adults, 17 (14.8%) experienced falls in the current institution. None of the HRV indices during the orthostatic challenge showed any significant changes except for the standard deviation of normal RR intervals (p = .037) in the institutionalized older adults with MCI. None of the HRV indices was significantly related to the depressive symptoms. Multivariate logistic regression analysis showed that normalized high frequency on lying was independently associated with falls (OR = 1.027, p = .049) after adjusting for other conventional fall risk factors although executive function and depressive symptoms were not significant factors for falls.

CONCLUSIONS

Institutionalized older adults with MCI were vulnerable to autonomic nervous modulation, especially to sympathetic modulation, during the orthostatic challenge, which was not associated with depressive symptoms. As increased resting parasympathetic activity seemed to play a key role in association with falls, autonomic nervous function assessment should be considered for fall risk evaluation.

Comparative Analysis of Fall Risk Assessment Features in Community-Elderly and Stroke Survivors: Insights from Sensor-Based Data

Fall-risk assessment studies generally focus on identifying characteristics that affect postural balance in a specific group of subjects. However, falls affect a multitude of individuals. Among the groups with the most recurrent fallers are the community-dwelling elderly and stroke survivors. Thus, this study focuses on identifying a set of features that can explain fall risk for these two groups of subjects. Sixty-five community dwelling elderly (forty-nine female, sixteen male) and thirty-five stroke-survivors (twenty-two male, thirteen male) participated in our study. With the use of an inertial sensor, some features are extracted from the acceleration data of a Timed Up and Go (TUG) test performed by both groups of individuals. A short-form berg balance scale (SFBBS) score and the TUG test score were used for labeling the data. With the use of a 100-fold cross-validation approach, Relief-F and Extra Trees Classifier algorithms were used to extract sets of the top 5, 10, 15, 20, 25, and 30 features. Random Forest classifiers were trained for each set of features. The best models were selected, and the repeated features for each group of subjects were analyzed and discussed. The results show that only the stand duration was an important feature for the prediction of fall risk across all clinical tests and both groups of individuals.

Pilot Study for Correlation of Heart Rate Variability and Dopamine Transporter Brain Imaging in Patients with Parkinsonian Syndrome

Background: Parkinsonian syndrome (PS) is a broad category of neurodegenerative movement disorders that includes Parkinson disease, multiple system atrophy (MSA), progressive supranuclear palsy, and corticobasal degeneration. Parkinson disease (PD) is the second most common neurodegenerative disorder with loss of dopaminergic neurons of the substantia nigra and, thus, dysfunction of the nigrostriatal pathway. In addition to the motor symptoms of bradykinesia, rigidity, tremors, and postural instability, nonmotor symptoms such as autonomic dysregulation (AutD) can also occur. Heart rate variability (HRV) has been used as a measure of AutD and has shown to be prognostic in diseases such as diabetes mellitus and cirrhosis, as well as PD. I-123 ioflupane, a gamma ray-emitting radiopharmaceutical used in single-photon emission computed tomography (SPECT), is used to measure the loss of dopaminergic neurons in PD. Through the combination of SPECT and HRV, we tested the hypothesis that asymmetrically worse left-sided neuronal loss would cause greater AutD. Methods: 51 patients were enrolled on the day of their standard of care I-123 ioflupane scan for the work-up of possible Parkinsonian syndrome. Demographic information, medical and medication history, and ECG data were collected. HRV metrics were extracted from the ECG data. I-123 ioflupane scans were interpreted by a board-certified nuclear radiologist and quantified by automated software to generate striatal binding ratios (SBRs). Statistical analyses were performed to find correlations between the HRV and SPECT parameters. Results: 32 patients were excluded from the final analysis because of normal scans, prior strokes, cardiac disorders and procedures, or cancer. Abnormal I-123 ioflupane scans were clustered using T-SNE, and one-way ANOVA was performed to compare HRV and SBR parameters. The analysis was repeated after the exclusion of patients taking angiotensin-converting enzyme inhibitors, given the known mechanism on autonomic function. Subsequent analysis showed a significant difference between the high-frequency domains of heart rate variability, asymmetry of the caudate SBR, and putamen-to-caudate SBR. Conclusion: Our results support the hypothesis that more imbalanced (specifically worse left-sided) neuronal loss results in greater AutD.

Wearable Sensors for Vital Signs Measurement: A Survey

With the outbreak of coronavirus disease-2019 (COVID-19) worldwide, developments in the medical field have aroused concerns within society. As science and technology develop, wearable medical sensors have become the main means of medical data acquisition. To analyze the intelligent development status of wearable medical sensors, the current work classifies and prospects the application status and functions of wireless communication wearable medical sensors, based on human physiological data acquisition in the medical field. By understanding its working principles, data acquisition modes and action modes, the work chiefly analyzes the application of wearable medical sensors in vascular infarction, respiratory intensity, body temperature, blood oxygen concentration, and sleep detection, and reflects the key role of wearable medical sensors in human physiological data acquisition. Further exploration and prospecting are made by investigating the improvement of information security performance of wearable medical sensors, the improvement of biological adaptability and biodegradability of new materials, and the integration of wearable medical sensors and intelligence-assisted rehabilitation. The research expects to provide a reference for the intelligent development of wearable medical sensors and real-time monitoring of human health in the follow-up medical field.

Remote Monitoring of Chronic Critically Ill Patients after Hospital Discharge: A Systematic Review

Background: Over the past few decades, critical care has seen many advancements. These advancements resulted in a considerable increase in the prevalence of chronically critically ill patients requiring prolonged medical care, which led to a massive increase in healthcare utilization. Methods: We performed a search for suitable articles using PubMed and Google Scholar from the inception of these databases to 15 May 2021. Results: Thirty-four articles were included in the review and analyzed. We described the following characteristics and problems with chronic critically ill patient management: the patient population, remote monitoring, the monitoring of physiological parameters in chronic critically ill patients, the anatomical location of sensors, the barriers to implementation, and the main technology-related issues. The main challenges in the management of these patients are (1) the shortage of caretakers, (2) the periodicity of vital function monitoring (e.g., episodic measuring of blood pressure leads to missing important critical events such as hypertension, hypotension, and hypoxia), and (3) failure to catch and manage critical physiological events at the right time, which can result in poor outcomes. Conclusions: The prevalence of critically ill patients is expected to grow. Technical solutions can greatly assist medical personnel and caregivers. Wearable devices can be used to monitor blood pressure, heart rate, pulse, respiratory rate, blood oxygen saturation, metabolism, and central nervous system function. The most important points that should be addressed in future studies are the performance of the remote monitoring systems, safety, clinical and economic outcomes, as well as the acceptance of the devices by patients, caretakers, and healthcare professionals.

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.

Effect of Workstation Type on the Relationship Between Fatigue, Physical Activity, Stress, and Sleep

OBJECTIVE

This study examined office workstation types' impact on the relationship between fatigue and three health metrics: physical activity, stress, and sleep quality.

METHODS

Data from 225 office workers were collected for perceived fatigue, perceived sleep quality (Pittsburgh Sleep Quality Index [PSQI]), physiological stress response (standard deviation of heart rate variability [HRV]), and physical activity (total activity in minutes) during three consecutive workdays. Stress and physical activity were measured using chest-worn sensors. Workers were then categorized as tired or not-tired based on the median of the fatigue rating.

RESULTS

Among tired workers, open-bench seating workers had increased physical activity, improved sleep quality, and reduced stress compared with workers in private offices and cubicles.

CONCLUSIONS

Office workstation types influence physical activity and levels of stress during work hours, which in turn affect sleep quality.

Harnessing digital health to objectively assess cancer-related fatigue: The impact of fatigue on mobility performance

Objective

Cancer-related fatigue (CRF) is highly prevalent among cancer survivors, which may have long-term effects on physical activity and quality of life. CRF is assessed by self-report or clinical observation, which may limit timely diagnosis and management. In this study, we examined the effect of CRF on mobility performance measured by a wearable pendant sensor.

Methods

This is a secondary analysis of a clinical trial evaluating the benefit of exercise in cancer survivors with chemotherapy-induced peripheral neuropathy (CIPN). CRF status was classified based on a Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-F) score ≤ 33. Among 28 patients (age = 65.7±9.8 years old, BMI = 26.9±4.1kg/m², sex = 32.9%female) with database variables of interest, twenty-one subjects (75.9%) were classified as non-CRF. Mobility performance, including behavior (sedentary, light, and moderate to vigorous activity (MtV)), postures (sitting, standing, lying, and walking), and locomotion (e.g., steps, postural transitions) were measured using a validated pendant-sensor over 24-hours. Baseline psychosocial, Functional Assessment of Cancer Therapy–General (FACT-G), Falls Efficacy Scale–International (FES-I), and motor-capacity assessments including gait (habitual speed, fast speed, and dual-task speed) and static balance were also performed.

Results

Both groups had similar baseline clinical and psychosocial characteristics, except for body-mass index (BMI), FACT-G, FACIT-F, and FES-I (p<0.050). The groups did not differ on motor-capacity. However, the majority of mobility performance parameters were different between groups with large to very large effect size, Cohen’s d ranging from 0.91 to 1.59. Among assessed mobility performance, the largest effect sizes were observed for sedentary-behavior (d = 1.59, p = 0.006), light-activity (d = 1.48, p = 0.009), and duration of sitting+lying (d = 1.46, p = 0.016). The largest correlations between mobility performance and FACIT-F were observed for sitting+lying (rho = -0.67, p<0.001) and the number of steps per day (rho = 0.60, p = 0.001).

Conclusion

The results of this study suggest that sensor-based mobility performance monitoring could be considered as a potential digital biomarker for CRF assessment. Future studies warrant evaluating utilization of mobility performance to track changes in CRF over time, response to CRF-related interventions, and earlier detection of CRF.

Current Evidence for Continuous Vital Signs Monitoring by Wearable Wireless Devices in Hospitalized Adults: Systematic Review

BACKGROUND

Continuous monitoring of vital signs by using wearable wireless devices may allow for timely detection of clinical deterioration in patients in general wards in comparison to detection by standard intermittent vital signs measurements. A large number of studies on many different wearable devices have been reported in recent years, but a systematic review is not yet available to date.

OBJECTIVE

The aim of this study was to provide a systematic review for health care professionals regarding the current evidence about the validation, feasibility, clinical outcomes, and costs of wearable wireless devices for continuous monitoring of vital signs.

METHODS

A systematic and comprehensive search was performed using PubMed/MEDLINE, EMBASE, and Cochrane Central Register of Controlled Trials from January 2009 to September 2019 for studies that evaluated wearable wireless devices for continuous monitoring of vital signs in adults. Outcomes were structured by validation, feasibility, clinical outcomes, and costs. Risk of bias was determined by using the Mixed Methods Appraisal Tool, quality assessment of diagnostic accuracy studies 2nd edition, or quality of health economic studies tool.

RESULTS

In this review, 27 studies evaluating 13 different wearable wireless devices were included. These studies predominantly evaluated the validation or the feasibility outcomes of these devices. Only a few studies reported the clinical outcomes with these devices and they did not report a significantly better clinical outcome than the standard tools used for measuring vital signs. Cost outcomes were not reported in any study. The quality of the included studies was predominantly rated as low or moderate.

CONCLUSIONS

Wearable wireless continuous monitoring devices are mostly still in the clinical validation and feasibility testing phases. To date, there are no high quality large well-controlled studies of wearable wireless devices available that show a significant clinical benefit or cost-effectiveness. Such studies are needed to help health care professionals and administrators in their decision making regarding implementation of these devices on a large scale in clinical practice or in-home monitoring.

Effect of wearables on sleep in healthy individuals: a randomized crossover trial and validation study

STUDY OBJECTIVES

The purpose of this study was to determine whether a wearable sleep-tracker improves perceived sleep quality in healthy participants and to test whether wearables reliably measure sleep quantity and quality compared with polysomnography.

METHODS

This study included a single-center randomized crossover trial of community-based participants without medical conditions or sleep disorders. A wearable device (WHOOP, Inc.) was used that provided feedback regarding sleep information to the participant for 1 week and maintained sleep logs versus 1 week of maintained sleep logs alone. Self-reported daily sleep behaviors were documented in sleep logs. Polysomnography was performed on 1 night when wearing the wearable. The Patient-Reported Outcomes Measurement Information System sleep disturbance sleep scale was measured at baseline, day 7 and day 14 of study participation.

RESULTS

In 32 participants (21 women; 23.8 ± 5 years), wearables improved nighttime sleep quality (Patient-Reported Outcomes Measurement Information System sleep disturbance: B = -1.69; 95% confidence interval, -3.11 to -0.27; P = .021) after adjusting for age, sex, baseline, and order effect. There was a small increase in self-reported daytime naps when wearing the device (B = 3.2; SE, 1.4; P = .023), but total daily sleep remained unchanged (P = .43). The wearable had low bias (13.8 minutes) and precision (17.8 minutes) errors for measuring sleep duration and measured dream sleep and slow wave sleep accurately (intraclass coefficient, 0.74 ± 0.28 and 0.85 ± 0.15, respectively). Bias and precision error for heart rate (bias, -0.17%; precision, 1.5%) and respiratory rate (bias, 1.8%; precision, 6.7%) were very low compared with that measured by electrocardiogram and inductance plethysmography during polysomnography.

CONCLUSIONS

In healthy people, wearables can improve sleep quality and accurately measure sleep and cardiorespiratory variables.

CLINICAL TRIAL REGISTRATION

Registry: ClinicalTrials.gov; Name: Assessment of Sleep by WHOOP in Ambulatory Subjects; Identifier: NCT03692195.

Using wearables to screen motor performance deterioration because of cancer and chemotherapy-induced peripheral neuropathy (CIPN) in adults - Toward an early diagnosis of CIPN

OBJECTIVE

An essential component for optimizing quality of life in adults with cancer is determining the degree to which therapy may negatively impact motor-performance, so that patients can maintain their quality of life and independence. This study examined whether instrumented gait and balance could determine the magnitude of deterioration in motor-performance from chemotherapy-induced peripheral neuropathy (CIPN).

METHODS

We recruited 84 adults with cancer (age = 71.1 ± 9.7 years old, BMI = 26.8 ± 6.2 kg/m², gender = 56%female) and 57 age-matched non-cancer patients (age = 69.5 ± 9.8 years old, BMI = 27.1 ± 6.0 kg/m², gender = 79%female). Based on clinical screening, the group with cancer was classified into two groups: participants with CIPN (CIPN+) and without CIPN (CIPN-). Gait and balance were quantified using validated wearables. The Vibration Perception Threshold (VPT) test was used to stratify the CIPN+ group into mild (Mild-CIPN) and severe (Severe-CIPN) subgroups.

RESULTS

All gait and balance parameters were deteriorated in the group with cancer compared to non-cancer group with the largest effects observed for stride-time (11%, Cohen's effect size d = 1.00, p < 0.001) and eyes-closed ankle sway (94%, d = 0.49, p = 0.001). The same trend was observed when the Severe-CIPN subgroup was compared to the Mild-CIPN. VPT correlates significantly with motor deterioration, with the largest correlation found in stride-time (Rho = 0.37, p = 0.007). Severe-CIPN subjects were significantly older and overall had more deterioration in the majority of motor-performance parameters after adjusting for age (p < 0.050).

CONCLUSION

These results confirmed the negative impact of CIPN on motor-performance with the largest effects on ankle stability and stride-time. VPT is a predictor of motor deterioration and may be used to determine the severity of CIPN symptom.

Complexity of Daily Physical Activity Is More Sensitive Than Conventional Metrics to Assess Functional Change in Younger Older Adults

The emerging mHealth applications, incorporating wearable sensors, enables continuous monitoring of physical activity (PA). This study aimed at analyzing the relevance of a multivariate complexity metric in assessment of functional change in younger older adults. Thirty individuals (60–70 years old) participated in a 4-week home-based exercise intervention. The Community Balance and Mobility Scale (CBMS) was used for clinical assessment of the participants’ functional balance and mobility performance pre- and post- intervention. Accelerometers worn on the low back were used to register PA of one week before and in the third week of the intervention. Changes in conventional univariate PA metrics (percentage of walking and sedentary time, step counts, mean cadence) and complexity were compared to the change as measured by the CBMS. Statistical analyses (21 participants) showed significant rank correlation between the change as measured by complexity and CBMS (ρ = 0.47, p = 0.03). Smoothing the activity output improved the correlation (ρ = 0.58, p = 0.01). In contrast, change in univariate PA metrics did not show correlations. These findings demonstrate the high potential of the complexity metric being useful and more sensitive than conventional PA metrics for assessing functional changes in younger older adults.

Motor Planning Error: Toward Measuring Cognitive Frailty in Older Adults Using Wearables

Practical tools which can be quickly administered are needed for measuring subtle changes in cognitive–motor performance over time. Frailty together with cognitive impairment, or ‘cognitive frailty’, are shown to be strong and independent predictors of cognitive decline over time. We have developed an interactive instrumented trail-making task (iTMT) platform, which allows quantification of motor planning error (MPE) through a series of ankle reaching tasks. In this study, we examined the accuracy of MPE in identifying cognitive frailty in older adults. Thirty-two older adults (age = 77.3 ± 9.1 years, body-mass-index = 25.3 ± 4.7 kg/m², female = 38%) were recruited. Using either the Mini-Mental State Examination or Montreal Cognitive Assessment (MoCA), 16 subjects were classified as cognitive-intact and 16 were classified as cognitive-impaired. In addition, 12 young-healthy subjects (age = 26.0 ± 5.2 years, body-mass-index = 25.3 ± 3.9 kg/m², female = 33%) were recruited to establish a healthy benchmark. Subjects completed the iTMT, using an ankle-worn sensor, which transforms ankle motion into navigation of a computer cursor. The iTMT task included reaching five indexed target circles (including numbers 1-to-3 and letters A&B placed in random order) on the computer-screen by moving the ankle-joint while standing. The ankle-sensor quantifies MPE through analysis of the pattern of ankle velocity. MPE was defined as percentage of time deviation between subject’s maximum ankle velocity and the optimal maximum ankle velocity, which is halfway through the reaching pathway. Data from gait tests, including single task and dual task walking, were also collected to determine cognitive–motor performance. The average MPE in young-healthy, elderly cognitive-intact, and elderly cognitive-impaired groups was 11.1 ± 5.7%, 20.3 ± 9.6%, and 34.1 ± 4.2% (p < 0.001), respectively. Large effect sizes (Cohen’s d = 1.17–4.56) were observed for discriminating between groups using MPE. Significant correlations were observed between the MPE and MoCA score (r = −0.670, p < 0.001) as well as between the MPE and dual task stride velocity (r = −0.584, p < 0.001). This study demonstrated feasibility and efficacy of estimating MPE from a practical wearable platform with promising results in identifying cognitive–motor impairment and potential application in assessing cognitive frailty. The proposed platform could be also used as an alternative to dual task walking test, where gait assessment may not be practical. Future studies need to confirm these observations in larger samples.

Improving Sleep Quality Assessment Using Wearable Sensors by Including Information From Postural/Sleep Position Changes and Body Acceleration: A Comparison of Chest-Worn Sensors, Wrist Actigraphy, and Polysomnography

STUDY OBJECTIVES

To improve sleep quality assessment using a single chest-worn sensor by extracting body acceleration and sleep position changes.

METHODS

Sleep patterns of 21 participants (50.8 ± 12.8 years, 47.8% female) with self-reported sleep problems were simultaneously recorded using a chest sensor (Chest), an Actiwatch (Wrist), and polysomnography (PSG) during overnight sleep laboratory assessment. An algorithm for Chest was developed to detect sleep/wake epochs based on body acceleration and sleep position/postural changes data, which were then used to estimate sleep parameters of interest. Comparisons between Chest and Wrist with respect to PSG were performed. Identification of sleep/wake epochs was assessed by estimating sensitivity, specificity, and accuracy. Agreement between sensor-derived sleep parameters and PSG was assessed using correlation coefficients and Bland-Altman analysis.

RESULTS

Chest identified sleep/wake epochs with an accuracy of on average 6% higher than Wrist (85.8% versus 79.8%). Similar trends were observed for sensitivity/specificity values. Correlation between Wrist and PSG was poor for most of the sleep parameters of interest (r = 0.0-0.3); however, Chest and PSG correlation showed moderate to strong agreement (r = 0.4-0.8) with relatively low bias and high precision bias (precision): 9.2 (13.2) minutes for sleep onset latency; 17.3(34.8) minutes for total sleep time; 7.5 (29.8) minutes for wake after sleep onset; and 2.0 (7.3)% for sleep efficacy.

CONCLUSIONS

Combination of sleep postural/position changes and body acceleration improved detection of sleep/wake epochs compared to wrist acceleration alone. The chest sensors also improved estimation of sleep parameters of interest with stronger agreement with PSG. Our findings may expand the application of wearable sensors to clinically assess sleep outside of a sleep laboratory.