Physiological Measurements.docx

Background. Mobility impairment is common in older adults and negatively influences the quality of life. Mobility level may change rapidly following surgery or hospitalization in the elderly. The Timed Up and Go (TUG) is a simple, frequently used clinical test for functional mobility; however, TUG requires supervision from a trained clinician, resulting in infrequent assessments. Additionally, assessment by TUG in clinic settings may not be completely representative of the individual’s mobility in their home environment. Objective. In this paper, we introduce a method to estimate TUG from activities detected in free-living, enabling continuous remote mobility monitoring without expert supervision. The method is used to monitor changes in mobility following Total Hip Arthroplasty (THA). Methods. Community-living elderly (n=239, 65-91 years) performed a standardized TUG in a laboratory and wore a wearable pendant device that recorded accelerometer and barometric sensor data for at least 3-days. Activities of daily living, including walks and sit-to-stand transitions, and their related mobility features were extracted and used to develop a regularized linear model for remote TUG test estimation. Changes in the remote TUG were evaluated in orthopaedic patients (n=15, 55-75 years), during 12-weeks following THA. Results. In leave-one-out-cross-validation, a strong correlation (ρ=0.70) was observed between the new remote TUG and standardized TUG times. Test-retest reliability of 3-day estimates was high (ICC=0.94). Compared to 2-weeks post-THA, remote TUG was significantly improved at 6-weeks (11.7±3.9 s vs 8.0±1.8 s, p<0.001), with no further change at 12-weeks (8.1±3.9 s, p=0.37). Conclusions. Remote TUG can be estimated in older adults using 3-days of ADLs data recorded using a wearable pendant. Remote TUG has discriminatory potential for identifying frail elderly and may provide a convenient way to monitor changes in mobility in unsupervised settings. Introduction Mobility is a key factor in healthy aging [1]. Mobility impairment is defined by a reduced postural balance and gait performance [2] that affects the ability to participate in activities of daily living (ADLs). Mobility impairment is common in the elderly population and it negatively influences the physical, psychological, and social wellness of older adults. Clinical review suggests primary care physicians should consider mobility as an essential aspect of the assessment of the frail older adult [3]. The Timed up and go test (TUG) is an established method to assess functional mobility, widely used in the literature as well as in the senior care industry [4, 5, 6]. The TUG test consists of getting up from a chair, walking 3-meters, turning 180 degrees, walking back to the chair, and sitting down [2]. The time to complete the task is recorded by a stopwatch and evaluated as test score; longer durations are associated with decreased mobility, and with adverse outcomes in the community-dwelling, as well as in institutionalized older adults [4]. The TUG-test has been widely cited in the literature as an outcome measure in a variety of conditions influencing mobility including stroke [7], chronic obstructive pulmonary disease [8] and Parkinson’s disease [9]. Moreover, TUG has been recommended for assessment of walking and balance in guidelines for fall prevention [10]. The TUG test is generally carried out under supervision in clinic setting. Due to resources constraints, the TUG test is often administered at a one-time point only, which may limit its ability to detect changes in mobility over time. Mobility may change rapidly in older adults, especially after hospital discharge [11] or during rehabilitation after orthopaedic surgery [12, 13, 14]. Whereas close supervision generally allows healthcare professionals to track changing mobility in hospitalized patients, tracking outpatients typically relies on less frequent physical examinations during clinical visits or self-reported questionnaires [14]. There is an unmet need for a cost-effective and objective way to remotely assess changes in mobility in unsupervised settings. Wearable sensor-based measurements [15] may provide valid and reliable data about physical activity in different hospital discharged populations such as people who have had a stroke [16], joint replacement [14], or cardiac surgery [11]. Systematic reviews have concluded that objective physical activity data collected by body-worn sensors may be capable of predicting functional recovery post-operatively [17]. Indicators of functional mobility during daily life include cumulative physical activity such as step counts [14], the ability to perform different ADLs such as chair rise transfers [18] and walking quality [19]. However, it is currently unclear how best to summarize the variety of sensor-based measures into a single mobility outcome that clinicians are familiar with and that can be easily interpreted. In this paper, a novel method for estimating mobility as TUG test value from ADLs recorded using a wearable pendant in free-living conditions is proposed. The method relies on the statistical relationships between mobility indicators measured in free-living conditions and the measured TUG test value, as observed in a population of older adults with a wide range of functional mobility. We aim also to gain insight into the clinical relevance of the proposed model; by examining free-living mobility data collected during 12 weeks in 15 patients recovering from Total Hip Arthroplasty (THA). Methods Study population For the remote TUG model development, a population of older people (total n=319) was recruited from Sydney, Australia (n=159); Cologne, Germany (n=25); Valencia, Spain (n=21) and Eindhoven, The Netherlands (n=114) respectively (Table 1). Participants from Australia, Germany, and Spain took part in the SureStep, iStoppFalls [20] and StandingTall [21] randomized controlled trials to prevent falls. Participants from The Netherlands were discharged patients who had been admitted for non-surgical reasons (Eindhoven). Individuals were eligible if they were: (i) Aged 65 years or older; (ii) living independently; (iii) able to walk with or without a walking aid. Exclusion criteria were: (i) Major cognitive impairments; (ii) medical conditions preventing regular exercise. For the assessment of changing mobility following surgery, volunteers participating in a post-THA rehabilitation program (n=20) were recruited at the Department of Orthopaedics, University Medical Centre Groningen, The Netherlands (Table 1). The THA participants underwent a THA as treatment for primary or secondary osteoarthritis. Patients were discharged a few days after surgery, in line with clinical practice in the Netherlands. Study participants followed a 12-week home-based exercise program with video instructions on a tablet PC. Patients performed strengthening and walking exercises at least five days a week [22] [23]. Daily activity assessments. Participants were required to wear the Senior Mobility Monitor (SMM) (Philips Research, Eindhoven, The Netherlands) in their usual environment during their normal ADLs, with no restriction for indoor or outdoor activities. The SMM was worn on a lanyard in front of the chest. The SMM (Figure 1) is a pendant containing a tri-axial-accelerometer and a barometer (approximate size: 39 x 12 x 63 mm). Accelerations were recorded at a sampling frequency of 50 Hz and with a dynamic range of ±8 g; air pressure, negatively correlated with height, was recorded with a sampling frequency of 25 Hz.