Treadmill training and/or body weight support may not improve walking ability following stroke

Summary of Moseley AM, Stark A, Cameron ID and Pollock A (2003): Treadmill training and body weight support for walking after stroke

Reliabilitet av den norske versjonen av Timed Up and Go (TUG)

Hensikt: Vurdere intratester-, intertester-, og test-retest reliabilitet av den norske versjonen av «Timed Up and Go» (TUG). Design: Metodestudie som benytter tverrsnittsstudie-design. Materiale og metode: Tretti personer (20 kvinner og 10 menn) over 75 år (gjennomsnitt 82,5) gjennomførte TUG tre ganger. To fysioterapeuter skåret deltagerne. For utregning av relativ reliabilitet ble intraclass correlation coefficient (ICC) anvendt, og for utregning av absolutt reliabilitet ble intrasubject standard deviation (Sw) anvendt. Resultater: Gjennomsnittstiden ble noe lavere ved hver gjennomføring, fra 20,2 til 18,1 sekunder. Intratester- og intertesterreliabilitet målt med ICC(1,1) viste 0,99 for alle målinger. 1,96 Sw varierte fra ±0,5 til er ±1,1 sekund mellom testerne for intratesterreliabilitet, og var ±0,3 sekunder for intertesterreliabilitet. Alle ICC(1,1) verdiene for test-retest var høyere enn 0,81 og 1,96 Sw varierte fra ±3,5 til ±4,4 sekunder. Reliabilitet ved gjennomsnittet av to målinger ICC(1,2) var over 0,90. Konklusjon: Studien viser at den nye norske protokollen av TUG har meget god intratester-, intertester- og test-retest reliabilitet. For høyere relativ reliabilitet anbefaler vi at gjennomsnittet av to målinger benyttes i klinikken. Med endringene foreslått i forhold til instruksjon, tidtakingparametrene og bruk av gjennomsnittet av to målinger, anbefaler vi at den utbedrede norske protokollen tas i bruk i Norge. Nøkkelord: standardiserte tester, klinisk protokoll, reliabilitet

Spatiotemporal gait parameters for older adults – An interactive model adjusting reference data for gender, age, and body height

Introduction Since it is well documented that spatiotemporal gait parameters are affected by body size, it is of limited clinical value to compare individual scores against reference values without taking body size into consideration. For older adults, reference values have been presented in recent reports, but unfortunately the effect of body size on gait characteristics was not taken into account and neither prediction intervals nor percentile ranks were included. It is the aim of this study to present and assess a model where individual spatiotemporal gait parameter values for older adults can be compared to reference values adjusted for gender, age, and body height. Methods Reference gait data were collected from l464 older adults aged 69–80 years with no impairments believed to affect gait, stratified by gender, intermediately adjusted to a common body height using a pendulum model and entered into a simple regression model for each parameter with age as predictor. From the regression coefficients predicted gait parameter values could be back transformed to the individual body height of a new subject. Calculations were done using spreadsheet formulae and equations. Results A spreadsheet based graphical user interface (GUI) has been developed in Microsoft Excel® where individual spatiotemporal gait data is entered for comparison with reference data taking gender, age and body height into account, and returning predicted point estimates with confidence intervals, prediction intervals, and percentile ranks. Significance A GUI solution where individual spatiotemporal gait data is compared to reference data is feasible to researchers and for clinical use. To the best of our knowledge, this is the first model presented for comparison of basic gait parameters between individuals and reference data from older adults where gender, age, and body height are taken into account.publishedVersio

Comparison of programs for determining temporal-spatial gait variables from instrumented walkway data: PKmas versus GAITRite

BACKGROUND: Measurement of temporal-spatial gait variables is common in aging research with several methods available. This study investigated the differences in temporal-spatial gait outcomes derived from two different programs for processing instrumented walkway data. METHOD: Data were collected with GAITRite® hardware from 86 healthy older people and 44 older people four months following surgical repair of hip fracture. Temporal-spatial variables were derived using both GAITRite® and PKmas® processing programs from the same raw footfall data. RESULTS: The mean differences between the two programs for most variables were negligible, including for Speed (mean difference 0.3 ± 0.6 cm/sec, or 0.3% of the mean GAITRite® Speed). The mean absolute percentage difference for all 18 gait variables examined ranged from 0.04% for Stride Duration to 66% for Foot Angle. The ICCs were almost perfect (≥0.99) for all variables apart from Base Width, Foot Angle, Stride Length Variability, Step Length Variability, Step Duration Variability and Step Width Variability, which were all never-the-less above 0.84. There were systematic differences for Base Width (PKmas® values 1.6 cm lower than GAITRite®) and Foot Angle (PKMAS® values 0.7° higher than GAITRite®). The differences can be explained by the differences in definitions and calculations between the programs. CONCLUSIONS: The study demonstrated that for most variables the outcomes from both programs can be used interchangeably for evaluation of gait among older people collected with GAITRite® hardware. However, validity and reliability for Base Width and Foot Angle derived by PKMAS® would benefit from further investigation

Impacts of COVID-19 restrictions on level of physical activity and health in home-dwelling older adults in Norway

Background - The spread of the coronavirus in spring 2020 led to a lockdown of physical activity (PA) offers. The aim of this study was to investigate how PA, as well as general and mental health, in community-dwelling older adults were affected by the COVID-19 restrictions in Norway. Methods - Invitation to participate in the study was sent via Facebook and the Norwegian Pensioners’ Association. Inclusion criteria were being ≥ 65 years old and living at home. Participants completed a questionnaire either digitally or on paper in June–August 2020. The questionnaire included questions on PA, general health, and mental health both before (13th of March) and during lockdown. Results - We included 565 participants (mean age 74 ± 5.3 years, 60.4% female); almost 60% had a university degree, 84% reported performing PA more than once per week, and 20% reported a fall in the previous 12 months. The Wilcoxon signed-rank test indicated that the corona lockdown significantly reduced activity level (Z = -4.918, p  Conclusions - In a relatively highly educated and active group of older participants, COVID-19 restrictions still negatively affected level of activity as well as general and mental health. These short-term decreases in activity level and health suggest that preventive actions and increased focus on measures to support older adults in maintaining an active lifestyle are needed

Physical Activity Classification for Elderly People in Free-Living Conditions

Physical activity is strongly linked with mental and physical health in the elderly population and accurate monitoring of activities of daily living (ADLs) can help improve quality of life and well-being. This study presents and validates an inertial sensors-based physical activity classification system developed with older adults as the target population. The dataset was collected in free-living conditions without placing constraints on the way and order of performing ADLs. Four sensor locations (chest, lower back, wrist, and thigh) were explored to obtain the optimal number and combination of sensors by finding the best tradeoff between the system's performance and wearability. Several feature selection techniques were implemented on the feature set obtained from acceleration and angular velocity signals to classify four major ADLs (sitting, standing, walking, and lying). A support vector machine was used for the classification of the ADLs. The findings show the potential of different solutions (single sensor or multisensor) to correctly classify the ADLs of older people in free-living conditions. Considering a minimal set-up of a single sensor, the sensor worn at the L5 achieved the best performance. A two-sensor solution (L5 + thigh) achieved a better performance with respect to a single-sensor solution. By contrast, considering more than two sensors did not provide further improvements. Finally, we evaluated the computational cost of different solutions and it was shown that a feature selection step can reduce the computational cost of the system and increase the system performance in most cases. This can be helpful for real-time applications.<br/

Exercise and rehabilitation delivered through exergames in older adults: An integrative review of technologies, safety and efficacy

Background: There has been a rapid increase in research on the use of virtual reality (VR) and gaming technology as a complementary tool in exercise and rehabilitation in the elderly population. Although a few recent studies have evaluated their efficacy, there is currently no in-depth description and discussion of different game technologies, physical functions targeted, and safety issues related to older adults playing exergames. Objectives: This integrative review provides an overview of the technologies and games used, progression, safety measurements and associated adverse events, adherence to exergaming, outcome measures used, and their effect on physical function. Methods: We undertook systematic searches of SCOPUS and PubMed databases. Key search terms included “game”, “exercise”, and “aged”, and were adapted to each database. To be included, studies had to involve older adults aged 65 years or above, have a pre-post training or intervention design, include ICT-implemented games with weight-bearing exercises, and have outcome measures that included physical activity variables and/or clinical tests of physical function. Results: Sixty studies fulfilled the inclusion criteria. The studies had a broad range of aims and intervention designs and mostly focused on community-dwelling healthy older adults. The majority of the studies used commercially available gaming technologies that targeted a number of different physical functions. Most studies reported that they had used some form of safety measure during intervention. None of the studies reported serious adverse events. However, only 21 studies (35%) reported on whether adverse events occurred. Twenty-four studies reported on adherence, but only seven studies (12%) compared adherence to exergaming with other forms of exercise. Clinical measures of balance were the most frequently used outcome measures. PEDro scores indicated that most studies had several methodological problems, with only 4 studies fulfilling 6 or more criteria out of 10. Several studies found positive effects of exergaming on balance and gait, while none reported negative effects. Conclusion: Exergames show promise as an intervention to improve physical function in older adults, with few reported adverse events. As there is large variability between studies in terms of intervention protocols and outcome measures, as well as several methodological limitations, recommendations for both practice and further research are provided in order to successfully establish exergames as an exercise and rehabilitation tool for older adults.© 2015 Elsevier Ireland Ltd. All rights reserved. This is the authors' accepted and refereed manuscript to the article. Locked until januar 2017-01-01 due to the copyright restrictions