Lorcan Walsh

Prevalence of sleep deficiency and use of hypnotic drugs in astronauts before, during, and after spaceflight: an observational study

BACKGROUND Sleep deprivation and fatigue are common subjective complaints among astronauts. Previous studies of sleep and hypnotic drug use in space have been limited to post-flight subjective survey data or in-flight objective data collection from a small number of crew members. We aimed to characterise representative sleep patterns of astronauts on both short-duration and long-duration spaceflight missions. METHODS For this observational study, we recruited crew members assigned to Space Transportation System shuttle flights with in-flight experiments between July 12, 2001, and July 21, 2011, or assigned to International Space Station (ISS) expeditions between Sept 18, 2006, and March 16, 2011. We assessed sleep-wake timing objectively via wrist actigraphy, and subjective sleep characteristics and hypnotic drug use via daily logs, in-flight and during Earth-based data-collection intervals: for 2 weeks scheduled about 3 months before launch, 11 days before launch until launch day, and for 7 days upon return to Earth. FINDINGS We collected data from 64 astronauts on 80 space shuttle missions (26 flights, 1063 in-flight days) and 21 astronauts on 13 ISS missions (3248 in-flight days), with ground-based data from all astronauts (4014 days). Crew members attempted and obtained significantly less sleep per night as estimated by actigraphy during space shuttle missions (7·35 h [SD 0·47] attempted, 5·96 h [0·56] obtained), in the 11 days before spaceflight (7·35 h [0·51], 6·04 h [0·72]), and about 3 months before spaceflight (7·40 h [0·59], 6·29 h [0·67]) compared with the first week post-mission (8·01 h [0·78], 6·74 h [0·91]; p<0·0001 for both measures). Crew members on ISS missions obtained significantly less sleep during spaceflight (6·09 h [0·67]), in the 11 days before spaceflight (5·86 h [0·94]), and during the 2-week interval scheduled about 3 months before spaceflight (6·41 h [SD 0·65]) compared with in the first week post-mission (6·95 h [1·04]; p<0·0001). 61 (78%) of 78 shuttle-mission crew members reported taking a dose of sleep-promoting drug on 500 (52%) of 963 nights; 12 (75%) of 16 ISS crew members reported using sleep-promoting drugs. INTERPRETATION Sleep deficiency in astronauts was prevalent not only during space shuttle and ISS missions, but also throughout a 3 month preflight training interval. Despite chronic sleep curtailment, use of sleep-promoting drugs was pervasive during spaceflight. Because chronic sleep loss leads to performance decrements, our findings emphasise the need for development of effective countermeasures to promote sleep. FUNDING The National Aeronautics and Space Administration.

Displacement of centre of mass during quiet standing assessed using accelerometry in older fallers and non-fallers

Postural sway during quiet standing is associated with falls risk in older adults. The aim of this study was to investigate the utility of a range of accelerometer-derived parameters of centre of mass (COM) displacement in identifying older adults at risk of falling. A series of instrumented standing balance trials were performed to investigate postural control in a group of older adults, categorised as fallers or non-fallers. During each trial, participants were asked to stand as still as possible under two conditions: comfortable stance (six repetitions) and semi-tandem stance (three repetitions). A tri-axial accelerometer was secured to the lower back during the trials. Accelerometer data were twice integrated to estimate COM displacement during the trials, with numerical techniques used to reduce integration error. Anterior-posterior (AP) and medial-lateral (ML) sway range, sway length and sway velocity were examined, along with root mean squared (RMS) acceleration. All derived parameters significantly discriminated fallers from non-fallers during both comfortable and semi-tandem stance. Results indicate that these accelerometer-based estimates of COM displacement may improve the discriminative power of quiet standing falls risk assessments, with potential for use in unsupervised balance assessment.

The reliability of the quantitative timed up and go test (QTUG) measured over five consecutive days under single and dual-task conditions in community dwelling older adults.

The timed up and go (TUG) test is a commonly used assessment in older people with variations including the addition of a motor or cognitive dual-task, however in high functioning older adults it is more difficult to assess change. The quantified TUG (QTUG) uses inertial sensors to detect test and gait parameters during the test. If it is to be used in the longitudinal assessment of older adults, it is important that we know which parameters are reliable and under which conditions. This study aims to examine the relative reliability of the QTUG over five consecutive days under single, motor and cognitive dual-task conditions. Twelve community dwelling older adults (10 females, mean age 74.17 (3.88)) performed the QTUG under three conditions for five consecutive days. The relative reliability of each of the gait parameters was assessed using intra-class correlation coefficient (ICC 3,1) and standard error of measurement (SEM). Five of the measures demonstrated excellent reliability (ICC>0.70) under all three conditions (time to complete test, walk time, number of gait cycles, number of steps and return from turn time). Measures of variability and turn derived parameters demonstrated weak reliability under all three conditions (ICC=0.05-0.49). For the most reliable parameters under single-task conditions, the addition of a cognitive task resulted in a reduction in reliability suggesting caution when interpreting results under these conditions. Certain sensor derived parameters during the QTUG test may provide an additional resource in the longitudinal assessment of older people and earlier identification of falls risk.

Quantitative falls risk estimation through multi-sensor assessment of standing balance

Falls are the most common cause of injury and hospitalization and one of the principal causes of death and disability in older adults worldwide. Measures of postural stability have been associated with the incidence of falls in older adults. The aim of this study was to develop a model that accurately classifies fallers and non-fallers using novel multi-sensor quantitative balance metrics that can be easily deployed into a home or clinic setting. We compared the classification accuracy of our model with an established method for falls risk assessment, the Berg balance scale. Data were acquired using two sensor modalities--a pressure sensitive platform sensor and a body-worn inertial sensor, mounted on the lower back--from 120 community dwelling older adults (65 with a history of falls, 55 without, mean age 73.7 ± 5.8 years, 63 female) while performing a number of standing balance tasks in a geriatric research clinic. Results obtained using a support vector machine yielded a mean classification accuracy of 71.52% (95% CI: 68.82-74.28) in classifying falls history, obtained using one model classifying all data points. Considering male and female participant data separately yielded classification accuracies of 72.80% (95% CI: 68.85-77.17) and 73.33% (95% CI: 69.88-76.81) respectively, leading to a mean classification accuracy of 73.07% in identifying participants with a history of falls. Results compare favourably to those obtained using the Berg balance scale (mean classification accuracy: 59.42% (95% CI: 56.96-61.88)). Results from the present study could lead to a robust method for assessing falls risk in both supervised and unsupervised environments.

An integrated home-based self-management system to support the wellbeing of older adults

With an ageing population and the constant need towards improving the quality of life for older people in our socie- ty, there comes an urgent challenge to support people where they live in an environment that adapts to their needs as they age. While much research on ubiquitous sensor systems and telehealth devices focuses on this need, many of these solutions operate at less than full capacity, and with little scope at present to assess everyday aspects of wellbeing. They focus on detecting sud- den critical physiological and behavioural changes and offer few mechanisms to support preventative actions. The challenge of predicting changes and prompting positive preventative intervention measures, aiding the avoidance of severe physical or men- tal harm, has not adequately been addressed. This paper discusses our experiences of designing, deploying and testing an inte- grated home-based ambient assisted living (AAL) system for older adults, consisting of ambient monitoring, behaviour recog- nition and feedback to support self-management of wellness, in addition to providing feedback on home security and home energy. It offers a complete system overview of an AAL solution in smart environments and discusses our lessons learned with the goal of assisting other researchers in the field in designing and deploying similar environments.

Identification of nocturnal movements during sleep using the non-contact under mattress bed sensor

This paper describes the calculation of statistical, spatial and spatiotemporal features from a novel non-contact technology for sleep monitoring, the Under Mattress Bed Sensor (UMBS). Data was collected from two relatively healthy adults with a possible sleep disorder in a clinical setting. Methods for the extraction of statistical data describing overall bed restlessness, a spatial description of movement (centre and spread of pressure) and a spatiotemporal description of each in-bed body movement over the entire sleeping episode are discussed using the pressure sensing grid. These provide a quantitative description of sleep and restlessness throughout the night.

Taking balance measurement out of the laboratory and into the home: Discriminatory capability of novel centre of pressure measurement in fallers and non-fallers

We investigated three methods for estimating centre of pressure excursions, as measured using a portable pressure sensor matrix, in order to deploy similar technology into the homes of older adults for longitudinal monitoring of postural control and falls risk. We explored the utility of these three methods as markers of falls risk in a cohort of 120 community dwelling older adults with and without a history of falls (65 fallers, 55 non-fallers). A number of standard quantitative balance parameters were derived using each centre of pressure estimation method. Rank sum tests were used to test for significant differences between fallers and non-fallers while intra-class correlation coefficients were also calculated to determine the reliability of each method. A method based on estimating the changes in the magnitude of pressure exerted on the pressure sensor matrix was found to be the most reliable and discriminative. Our future work will implement this method for home-based balance measurement.

The deployment of a non-intrusive alternative to sleep/wake wrist actigraphy in a home-based study of the elderly

This paper reports on experimental trials with an Under Mattress Bed Sensor (UMBS), an easily deployable, non-contact, low cost alternative to the actigraphy watch for sleep monitoring. Results from a home-based study of elderly subjects confirm accurate temporal resolution of activity monitoring in bed. UMBS activity classification thresholds were determined by maximizing Matthews Correlation Coefficient between the activity data captured using an actigraphy watch and the proposed sensor. Preliminary results on a healthy young subject showed very high agreement rates justifying its use as a replacement for wrist actigraphy.

Inferring health metrics from ambient smart home data

As the population ages, smart home technology and applications are expected to support older adults to age in place and reduce the associated economic and societal burden. This paper describes a study where the relationship between ambient sensors, permanently deployed as part of smart aware apartments, and clinically validated health questionnaires is investigated. 27 sets of ambient data were taken from a 28 day block from 13 participants all of whom were over 60 years old. Features derived from ambient sensor data were found to be significantly correlated to measures of anxiety, sleep quality, depression, loneliness, cognition, quality of life and independent living skills (IADL). Subsequently, linear discriminant analysis was shown to predict participants suffering from increased anxiety and loneliness with a high accuracy (≥70%). While the number of participants is small, this study reports that objective ambient features may be used to infer clinically validated health metrics. Such findings may be used to inform interventions for active and healthy ageing.

Does external walking environment affect gait patterns

The objective of this work is to develop an understanding of the relationship between mobility metrics obtained outside of the clinic or laboratory and the context of the external environment. Ten subjects walked with an inertial sensor on each shank and a wearable camera around their neck. They were taken on a thirty minute walk in which they mobilized over the following conditions; normal path, busy hallway, rough ground, blind folded and on a hill. Stride time, stride time variability, stance time and peak shank rotation rate during swing were calculated using previously published algorithms. Stride time was significantly different between several of the conditions. Technological advances mean that gait variables can now be captured as patients go about their daily lives. The results of this study show that the external environment has a significant impact on the quality of gait metrics. Thus, context of external walking environment is an important consideration when analyzing ambulatory gait metrics from the unsupervised home and community setting.