Marie Demonceau

Effects of 3 months of short sessions of controlled whole body vibrations on the risk of falls among nursing home residents

BackgroundFatigue, lack of motivation and low compliance can be observed in nursing home residents during the practice of physical activity. Because exercises should not be too vigorous, whole body vibration could potentially be an effective alternative. The objective of this randomized controlled trial was to assess the impact of 3-month training by whole body vibration on the risk of falls among nursing home residents.MethodsPatients were randomized into two groups: the whole body vibration group which received 3 training sessions every week composed of 5 series of only 15 seconds of vibrations at 30 Hz frequency and a control group with normal daily life for the whole study period. The impact of this training on the risk of falls was assessed blindly by three tests: the Tinetti Test, the Timed Up and Go test and a quantitative evaluation of a 10-second walk performed with a tri-axial accelerometer.Results62 subjects (47 women and 15 men; mean age 83.2 ± 7.99 years) were recruited for the study. No significant change in the studied parameters was observed between the treated (n=31) and the control group (n=31) after 3 months of training by controlled whole-body-vibrations. Actually, the Tinetti test increased of + 0.93 ± 3.14 points in the treated group against + 0.88 ± 2.33 points in the control group (p = 0.89 when adjusted). The Timed Up and Go test showed a median evolution of - 1.14 (− 4.75-3.73) seconds in the treated group against + 0.41 (− 3.57- 2.41) seconds in the control group (p = 0.06). For the quantitative evaluation of the walk, no significant change was observed between the treated and the control group in single task as well as in dual task conditions.ConclusionsThe whole body vibration training performed with the exposition settings such as those used in this research was feasible but seems to have no impact on the risk of falls among nursing home residents. Further investigations, in which, for example, the exposure parameters would be changed, seem necessary.Trial registrationTrial registration number: NCT01759680

Contribution of a Trunk Accelerometer System to the Characterization of Gait in Patients With Mild-to-Moderate Parkinson's Disease

Objective: Gait disturbances like shuffling and short steps are obvious at visual observation in patients with advanced Parkinsons disease (PD). However, quantitative methods are increasingly used to evaluate the wide range of gait abnormalities that may occur over the disease course. The goal of this study was to test the ability of a trunk accelerometer system to quantify the effects of PD on several gait features when walking at self-selected speed. Methods: We recruited 96 subjects split into three age-matched groups: 32 healthy controls (HC), 32 PD patients at Hoehn and Yahr stage <; II (PD-1), and 32 patients at Hoehn and Yahr stage II-III (PD-2). The following outcomes were extracted from the signals of the triaxial accelerometer worn on the lower back: stride length, cadence, regularity index, symmetry index, and mechanical powers yielded in the cranial-caudal, anteroposterior, and medial-lateral directions. Walking speed was measured using a stopwatch. Results: Besides other gait features, the PD-1 and the PD-2 groups showed significantly reduced stride length normalized to height (p <; 0.02) and symmetry index (p <; 0.009) in comparison to the HC. Regularity index was the only feature significantly decreased in the PD-2 group as compared with the two other groups (p <; 0.01). The clinical relevance of this finding was supported by significant correlations with mobility and gait scales (r is around -0.3; p <; 0.05). Conclusion: Gait quantified by a trunk accelerometer may provide clinically useful information for the screening and follow-up of PD patients.

Added value of a triaxial accelerometer assessing gait parameters to predict falls and mortality among nursing home residents: A two-year prospective study

BACKGROUND Gait impairment seems to be a risk factor for falls and mortality. Because gait change cannot be determined easily with classical clinical tests, some authors have suggested that it might be useful to use a gait-analysis system among elderly community-dwelling people. OBJECTIVE The main objective of the present study was to determine the predictive value of a quantitative evaluation of the gait characteristics in nursing home residents for the occurrence of falls and death performed using a tri-axial accelerometer (Locométrix®). MATERIAL AND METHODS One hundred elderly nursing home residents (80 women and 20 men, mean age 86.4 ± 6.04 years) were included in this study with the aim to follow them for 2 years. Deaths and falls were systematically recorded. A quantitative evaluation of a 10-second walk was performed with a tri-axial accelerometer (Locometrix®). Demographic data (i.e age, sex, body mass index) and clinical data (i.e. fall risk evaluated by the Tinetti test) were also recorded. RESULTS During the two years of follow-up, 27 patients died. After adjustment on all potential confounding variables, only body mass index was significantly associated with the risk of mortality with an odds ratio of 0.86 (95% CI: 0.77-0.96, p=0.04). At the end of the study period, 440 falls had occurred (mean: 4.44 ± 6.79 falls per patient) but no single factors were independently associated with fall incidence. CONCLUSION Our results show that a quantitative gait analysis performed using a tri-axial accelerometer is not predictive of long-term falls and mortality among nursing home residents.

Extraction of temporal gait parameters using a reduced number of wearable accelerometers

Wearable inertial systems often require many sensing units in order to reach an accurate extraction of temporal gait parameters. Reconciling easy and fast handling in daily clinical use and accurate extraction of a substantial number of relevant gait parameters is a challenge. This paper describes the implementation of a new accelerometer-based method that accurately and precisely detects gait events/parameters from acceleration signals measured from only two accelerometers attached on the heels of the subject’s usual shoes. The first step of the proposed method uses a gait segmentation based on the continuous wavelet transform (CWT) that provides only a rough estimation of motionless periods defining relevant local acceleration signals. The second step uses the CWT and a novel piecewise-linear fitting technique to accurately extract, from these local acceleration signals, gait events, each labelled as heel strike (HS), toe strike (TS), heel-off (HO), toe-off (TO), or heel clearance (HC). A stride-by-stride validation of these extracted gait events was carried out by comparing the results with reference data provided by a kinematic 3D analysis system (used as gold standard) and a video camera. The temporal accuracy ± precision of the gait events were for HS: 7.2 ms ± 22.1 ms, TS: 0.7 ms ± 19.0 ms, HO: −3.4 ms ± 27.4 ms, TO: 2.2 ms ± 15.7 ms, and HC: 3.2 ms ± 17.9 ms. In addition, the occurrence times of right/left stance, swing, and stride phases were estimated with a mean error of −6 ms ± 15 ms, −5 ms ± 17 ms, and −6 ms ± 17 ms, respectively. The accuracy and precision achieved by the extraction algorithm for healthy subjects, the simplification of the hardware (through the reduction of the number of accelerometer units required), and the validation results obtained, convince us that the proposed accelerometer-based system could be extended for assessing pathological gait (e.g., for patients with Parkinson’s disease).

Segmentation of gait cycles using foot-mounted 3D accelerometers

We describe a new gait segmentation method based on the continuous wavelet transform to identify stride-by-stride gait cycles from measurements of foot-mounted three-dimensional (3D) accelerometers. The detection of such gait cycles is indeed a crucial step for an accurate extraction of relevant gait events such as heel strike, toe strike, heel-off, and toe-off. We demonstrate the ability of this segmentation method, used in conjunction with a validated extraction algorithm, to calculate the following gait (duration) parameters for each gait cycle during the gait of a healthy young subject and of an elderly subject with Parkinsons disease (PD) in OFF and ON states: durations of (1) loading response, (2) mid-stance, (3) push-off, (4) stance, (5) swing, (6) stride, (7) step, and (8) double support phases. The experimental results show that the proposed method can extract relevant refined gait parameters to quantify subtle gait disturbances in subjects with PD.

Assessing gait parameters with accelerometer-based methods to identify older adults at risk of falls: a systematic review

PurposeThe purpose of this study was to perform a systematic review to assess the utility of accelerometric methods to identify older adults at risk of falls.MethodsThe Preferred Reporting Item for Systematic review and Meta-Analysis (PRISMA) guidelines were followed during all steps of this systematic review. Cross sectional and longitudinal studies assessing gait parameters in older adults using accelerometric devices, and comparing groups based on the risk of falls or fall history were identified from studies published in the MEDLINE, SCOPUS and Cochrane Database of Systematic Reviews databases between January 1996 and January 2017. Study selection and data extraction were performed independently by two reviewers. The quality of the methodology used in the studies included was assessed using the Newcastle–Ottawa Scale.ResultsIn total, 354 references were identified through the database search. After selection, ten studies were included in this systematic review. According to the cross sectional studies, people who fall or are at risk of fall are slower, and walk with shorter steps, lower step frequency, worse stride and step regularity in terms of time, position and acceleration profiles. One longitudinal study suggests considering harmonic ratio of upper trunk acceleration in the vertical plane. Two other longitudinal studies highlight the importance of considering more than one gait parameter, and sophisticated statistical tools to discern older adults at risk for future fall(s).ConclusionThis systematic review essentially highlights the lack of available literature providing strong evidence that gait parameters obtained using acceleration-based methods could be useful to discern older people at risk of fall. Available literature is encouraging, but further high quality studies are needed to highlight the cross-sectional and longitudinal relationships between gait parameters and falls in older adults.

Data set of healthy old people assessed for three walking conditions using accelerometric and opto-electronic methods

BackgroundGait patterns of healthy aging are needed to allow a comparison with pathological situations. However, little data is available.ObjectiveTo present gait pattern of healthy older specially selected to be “healthy walkers”.MethodFifty-seven older people benefited from a geriatric assessment including clinical and functional evaluations to include only those without gait disorders. Gait data were simultaneously recorded using a tri-axial accelerometer placed on the waist and four 3D position markers placed on the feet at the level of the heel and the toe. Volunteers walked at comfortable self-selected speed (CW), fast self-selected speed (FW), and finally in dual task walking condition (DTW). The extracted gait parameters were: gait speed, stride length, stride frequency, regularity and symmetry, swing, stance and double support time and ratio and minimum toe clearance. Gait speed and stride length were normalized to the right leg length.ResultsFifty-seven older people with a mean age of 69.7 ± 4.2 years old (range from 65 to 82 years) were included. Data were analyzed according to the gender and according to the age (<70 or ≥70 years old). After normalization to leg length, the main significant differences were shown for stride length and minimum toe clearance in CW, FW and in DTW that were shorter in women. The regularity in FW was significantly lower among older volunteers.ConclusionsThis work provides a data set considering 14 gait parameters obtained from 57 healthy old people strictly selected and assessed for three walking conditions and shows that GS, SL and MTC have to be related to the gender. The age-related impact on gait performances appears reduced in this cohort.

Algorithm for Temporal Gait Analysis Using Wireless Foot-Mounted Accelerometers

We present a new signal processing algorithm that extracts five gait events: heel strike, toe strike, heel-off, toe-off, and heel clearance from only two accelerometers attached on the heels of the subjects usual shoes. This algorithm first uses a continuous wavelet-based segmentation that parses the signal of consecutive strides into motionless periods defining relevant local acceleration signals. Then, the algorithm uses versatile techniques to accurately extract the five gait events from these local acceleration signals. We validated, on a stride-by-stride basis, the extraction of these gait events by comparing the results with reference data provided by a kinematic 3D analysis system and a video camera. The accuracy and precision achieved by the extraction algorithm for healthy subjects, the reduced number of accelerometer units required, and the validation results obtained, encourage us to further study this system in pathological conditions.

P-331: Baseline characteristics of a two-year prospective study aiming to link clinical components, cognitive and gait performances in healthy old people

Conclusions: To the best of our knowledge this is the first study that presents data on the relationship between smoking and life satisfaction of older people in EU countries living independently. Non-smoking older people report a higher level of life satisfaction compared to smoking older people. The relation between smoking behaviour, diseases, disabilities and life satisfaction is complicated because smoking is related to diseases with a high mortality rate and sometimes a relatively short period with disabilities before death.

Effects of twelve weeks of aerobic or strength training in addition to standard care in Parkinson’s disease: a controlled study

BACKGROUND Physical exercise in addition to standard care (SC) in patients with Parkinsons disease (PD) is now a common practice in many care units. However, exercises can cover a wide range of interventions, and the specific effects of different interventions still deserve to be further investigated. AIM The aim of this study was to compare the effects of 12 weeks of two different types of physical exercises with SC in patients suffering from PD. DESIGN Pseudo-randomized controlled trial. SETTING University laboratory for outcomes, University Hospital Centre for interventions. POPULATION Fifty-two outpatients suffering from mild to moderate PD at baseline. METHODS Participants were allocated to three groups: the strength training (ST) group performed individualized upper and lower limbs strength training, the aerobic training (AE) group performed tailored gradual aerobic cycling, and the third group received SC. The effects of the interventions on body function were assessed by measuring isokinetic concentric peak torque for knee extension and flexion, peak oxygen consumption (VO2peak) and peak work load (PWL) during an incremental maximal cycling test. Changes in mobility were evaluated from spatial-temporal gait features measured by mean of an accelerometer system and the Six-Minute Walk Distance (6MWD) Test. We used questionnaires to estimate health-related quality of life and habitual physical activity. RESULTS No significant changes in any outcome measures occurred in the SC group. More than 80% of the participants adequately completed the AE and the ST interventions. The ST group significantly improved all peak torque measures (P≤0.01), except knee extension in the least affected side (P=0.13). This group also improved the PWL (P=0.009) and 6mwd (P=0.03). The AE group improved the VO2peak (P=0.02) and PWL (P<0.001). CONCLUSIONS Physical fitness in patients with PD rapidly improved in compliance with training specificities, but better fitness hardly translated into better mobility and health-related quality of life. CLINICAL REHABILITATION IMPACT Physiotherapists can efficiently propose physical conditioning to patients with mild to moderate PD, but these interventions are insufficient to improve gait and participation. Notwithstanding, ST is an efficient intervention for improving walking capacity.