Remote timed up and go evaluation from activities of daily living reveals changing mobility after surgery

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 three days. Activities of daily living (ADLs), 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 period following THA. Main results: In leave-one-out-cross-validation (LOOCV), a strong correlation (p = 0.70) was observed between the new remote TUG and standardized TUG times. Test-retest reliability of 3-days estimates was high (ICC = 0.94). Compared to week 2 post-THA, remote TUG was significantly improved at week 6 (11.7 +/- 3.9 s versus 8.0 +/- 1.8 s,p &lt;0.001), with no further change at 12-weeks (8.1 +/- 3.9s, p = 0.37). Significance: 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.</p

A review of activity trackers for senior citizens: research perspectives, commercial landscape and the role of the insurance industry

The objective assessment of physical activity levels through wearable inertial-based motion detectors for the automatic, continuous and long-term monitoring of people in free-living environments is a well-known research area in the literature. However, their application to older adults can present particular constraints. This paper reviews the adoption of wearable devices in senior citizens by describing various researches for monitoring physical activity indicators, such as energy expenditure, posture transitions, activity classification, fall detection and prediction, gait and balance analysis, also by adopting consumer-grade fitness trackers with the associated limitations regarding acceptability. This review also describes and compares existing commercial products encompassing activity trackers tailored for older adults, thus providing a comprehensive outlook of the status of commercially available motion tracking systems. Finally, the impact of wearable devices on life and health insurance companies, with a description of the potential benefits for the industry and the wearables market, was analyzed as an example of the potential emerging market drivers for such technology in the future

New for old:Development and implementation of a home-based exercise intervention using novel remote technology for older adults

Regelmatige en voldoende lichamelijke activiteit is een voorwaarde voor het gezond ouder worden. Echter zijn de meeste mensen onvoldoende actief in het dagelijks leven. Zelfstandig thuis oefeningen doen wordt vaak de voorkeur aan gegeven boven activiteiten op locatie, echter ontbreekt thuis vaak toch de motivatie om oefeningen te doen. De ontwikkelingen in de moderne techniek bieden mogelijkheden om zelfstandig thuis te oefenen maar toch de voordelen te hebben van groepsactiviteiten of een begeleide training op locatie, door middel van het gebruik van beweegsensoren en een platform op de computer of tablet wat oefeningen aanbiedt en contact mogelijk maakt met andere mensen die oefeningen doen of een coach. In deze thesis is een thuis-beweegprogramma opgezet en getest, waarin ouderen een oefenprogramma werd aangeboden wat zij thuis uitvoerden. Daarbij droegen zij een beweegsensor die hun dagelijkse activiteit registreerde, en oefenden zij op hun eigen niveau met behulp van filmpjes op een tablet. Deze tablet registreerde hun activiteit en hoe veel zij oefenden. Een coach kon deze gegevens inzien en zowel de tablet applicatie zelf als de coach gaven de deelnemers persoonlijke feedback daarop. Een onderzoek waarin 40 kwetsbare ouderen een half jaar oefenden met dit programma geeft aan dat met name een zeer stabiele internetverbinding van belang was voor het slagen van de training. Zowel ervaren als onervaren tablet gebruikers zijn enthousiast over het programma en gebruik van de tablet en beweegsensor. Op dit moment wordt de technologie verder getest in een thuis-revalidatie programma voor mensen met een nieuwe knie of heup

Data Quality and Reliability Assessment of Wearable EMG and IMU Sensor for Construction Activity Recognition

The workforce shortage is one of the significant problems in the construction industry. To overcome the challenges due to workforce shortage, various researchers have proposed wearable sensor-based systems in the area of construction safety and health. Although sensors provide rich and detailed information, not all sensors can be used for construction applications. This study evaluates the data quality and reliability of forearm electromyography (EMG) and inertial measurement unit (IMU) of armband sensors for construction activity classification. To achieve the proposed objective, the forearm EMG and IMU data collected from eight participants while performing construction activities such as screwing, wrenching, lifting, and carrying on two different days were used to analyze the data quality and reliability for activity recognition through seven different experiments. The results of these experiments show that the armband sensor data quality is comparable to the conventional EMG and IMU sensors with excellent relative and absolute reliability between trials for all the five activities. The activity classification results were highly reliable, with minimal change in classification accuracies for both the days. Moreover, the results conclude that the combined EMG and IMU models classify activities with higher accuracies compared to individual sensor models

ICT-based system to predict and prevent falls (iStoppFalls): study protocol for an international multicenter randomized controlled trial

[EN] Background: Falls are very common, especially in adults aged 65 years and older. Within the current international European Commission's Seventh Framework Program (FP7) project 'iStoppFalls' an Information and Communication Technology (ICT) based system has been developed to regularly assess a person's risk of falling in their own home and to deliver an individual and tailored home-based exercise and education program for fall prevention. The primary aims of iStoppFalls are to assess the feasibility and acceptability of the intervention program, and its effectiveness to improve balance, muscle strength and quality of life in older people. Methods/Design: This international, multicenter study is designed as a single-blinded, two-group randomized controlled trial. A total of 160 community-dwelling older people aged 65 years and older will be recruited in Germany (n = 60), Spain (n = 40), and Australia (n = 60) between November 2013 and May 2014. Participants in the intervention group will conduct a 16-week exercise program using the iStoppFalls system through their television set at home. Participants are encouraged to exercise for a total duration of 180 minutes per week. The training program consists of a variety of balance and strength exercises in the form of video games using exergame technology. Educational material about a healthy lifestyle will be provided to each participant. Final reassessments will be conducted after 16 weeks. The assessments include physical and cognitive tests as well as questionnaires assessing health, fear of falling, quality of life and psychosocial determinants. Falls will be followed up for six months by monthly falls calendars. Discussion: We hypothesize that the regular use of this newly developed ICT-based system for fall prevention at home is feasible for older people. By using the iStoppFalls sensor-based exercise program, older people are expected to improve in balance and strength outcomes. In addition, the exercise training may have a positive impact on quality of life by reducing the risk of falls. Taken together with expected cognitive improvements, the individual approach of the iStoppFalls program may provide an effective model for fall prevention in older people who prefer to exercise at home.The authors are members of the iStoppFalls project. This project has received funding from the European Union’s Seventh Framework Programme for research, technological development, and demonstration under grant agreement no [287361]. The Australian arm is funded by an Australian National Health and Medical Research Council (NHMRC) EU collaboration grant (#1038210). The content of the manuscript does not represent the opinion of the European Community or NHMRC. The funding sources have no role in any aspects of this study. Yves J. Gschwind has been financially supported by a research grant from the Margarete and Walter Lichtenstein Foundation, Basel, Switzerland. Stephen R. Lord is supported by NHMRC as a Senior Principal Research Fellow and Kim Delbaere as a NHMRC Career Development Fellow. All other authors are supported by the iStoppFalls project, European Community Grant Agreement 287361. On behalf the iStoppFalls consortium, we would like to thank all the participants who take part in the study.Gschwind, YJ.; Eichberg, S.; Marston, HR.; Ejupi, A.; De Rosario Martínez, H.; Kroll, M.; Drobics, M.... (2014). ICT-based system to predict and prevent falls (iStoppFalls): study protocol for an international multicenter randomized controlled trial. BMC Geriatrics. 14(91):1-13. https://doi.org/10.1186/1471-2318-14-91S1131491Berchicci M, Lucci G, Di Russo F: Benefits of physical exercise on the aging brain: the role of the prefrontal cortex. 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Incident Depression and Daily-life Mobility in Middle-aged and Older Adults

Depression is among the most prevalent mental disorders in middle-aged and older adults, with a global prevalence of up to 11%. Effective preventive measures for depression are often costly and labour-intensive and therefore require risk screenings to be practical. Recent studies suggested that clinically measured walking speed is a risk factor for depression, while little is known about whether other aspects of mobility are also predictive. To explore the temporal association between mobility, in particular daily-life mobility, and incident depression in older adults, one systematic review, one study on method development and validation, and three large-scale cohort studies were conducted. Significant findings include: • The Timed Up and Go Test, which incorporates multiple aspects of mobility (i.e., gait initiation, turning, and sit-to-stand time), is more predictive of depressive trajectories than the Six-Metre Walk Test and Five Times Sit to Stand Test. • Duration of the longest daily walking bout, measured with a waist-worn sensor, independently and significantly predicts incident depression over two years. • Daily-life walking speed, quality, quantity, and distribution can be reliably and validly measured with a wrist-worn sensor. • Daily-life gait quality and quantity, measured with a wrist-worn sensor, independently and significantly predict incident depression over nine years of follow-up. These findings add to the understanding of the association between human locomotion and depression. Gait quality and daily-life gait performances are independent and potentially modifiable predictors of depression. These measures, therefore, may have value for upcoming screening program development. Future research should investigate whether interventions addressing daily-life gait can play a role in preventing depression in middle-aged and older adults

ICT-based system to predict and prevent falls (iStoppFalls): results from an international multicenter randomized controlled trial

Background: Falls and fall-related injuries are a serious public health issue. Exercise programs can effectively reduce fall risk in older people. The iStoppFalls project developed an Information and Communication Technology-based system to deliver an unsupervised exercise program in older people’s homes. The primary aims of the iStoppFalls randomized controlled trial were to assess the feasibility (exercise adherence, acceptability and safety) of the intervention program and its effectiveness on common fall risk factors. Methods: A total of 153 community-dwelling people aged 65+ years took part in this international, multicentre, randomized controlled trial. Intervention group participants conducted the exercise program for 16 weeks, with a recommended duration of 120 min/week for balance exergames and 60 min/week for strength exercises. All intervention and control participants received educational material including advice on a healthy lifestyle and fall prevention. Assessments included physical and cognitive tests, and questionnaires for health, fear of falling, number of falls, quality of life and psychosocial outcomes. Results: The median total exercise duration was 11.7 h (IQR = 22.0) over the 16-week intervention period. There were no adverse events. Physiological fall risk (Physiological Profile Assessment, PPA) reduced significantly more in the intervention group compared to the control group (F1,127 = 4.54, p = 0.035). There was a significant three-way interaction for fall risk assessed by the PPA between the high-adherence (>90 min/week; n = 18, 25.4 %), low-adherence (n = 53, 74.6 %) and control group (F2,125 = 3.12, n = 75, p = 0.044). Post hoc analysis revealed a significantly larger effect in favour of the high-adherence group compared to the control group for fall risk (p = 0.031), postural sway (p = 0.046), stepping reaction time (p = 0.041), executive functioning (p = 0.044), and quality of life (p for trend = 0.052). Conclusions: The iStoppFalls exercise program reduced physiological fall risk in the study sample. Additional subgroup analyses revealed that intervention participants with better adherence also improved in postural sway, stepping reaction, and executive function

Development of a real-time classifier for the identification of the Sit-To-Stand motion pattern

The Sit-to-Stand (STS) movement has significant importance in clinical practice, since it is an indicator of lower limb functionality. As an optimal trade-off between costs and accuracy, accelerometers have recently been used to synchronously recognise the STS transition in various Human Activity Recognition-based tasks. However, beyond the mere identification of the entire action, a major challenge remains the recognition of clinically relevant phases inside the STS motion pattern, due to the intrinsic variability of the movement. This work presents the development process of a deep-learning model aimed at recognising specific clinical valid phases in the STS, relying on a pool of 39 young and healthy participants performing the task under self-paced (SP) and controlled speed (CT). The movements were registered using a total of 6 inertial sensors, and the accelerometric data was labelised into four sequential STS phases according to the Ground Reaction Force profiles acquired through a force plate. The optimised architecture combined convolutional and recurrent neural networks into a hybrid approach and was able to correctly identify the four STS phases, both under SP and CT movements, relying on the single sensor placed on the chest. The overall accuracy estimate (median [95% confidence intervals]) for the hybrid architecture was 96.09 [95.37 - 96.56] in SP trials and 95.74 [95.39 \u2013 96.21] in CT trials. Moreover, the prediction delays ( 4533 ms) were compatible with the temporal characteristics of the dataset, sampled at 10 Hz (100 ms). These results support the implementation of the proposed model in the development of digital rehabilitation solutions able to synchronously recognise the STS movement pattern, with the aim of effectively evaluate and correct its execution

A influência imediata de estímulos auditivos na marcha de idosos com e sem a doença de Parkinson

Projeto de Graduação apresentado à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Licenciada em FisioterapiaObjetivo: Avaliar a influência imediata dos estímulos auditivos na marcha em idosos com e sem a Doença de Parkinson (DP). Metodologia: Amostra composta por 6 idosos com DP (77,67 ± 6,65 anos; 25,58 ± 2,07 kg/m2) e 6 idosos sem DP (80 ± 7,46 anos; 25,66 ± 1,18 kg/m2). Aos 12 participantes foram aplicados a Escala Unificada de Avaliação da DP, Berg Balance Scale, avaliação da cadência, e aplicação do Timed Up and Go Test (TUG), este último com e sem estímulo auditivo, de forma aleatória, verificando o tempo, o comprimento do passo e da passada. Resultados: Os idosos com DP apresentaram uma cadência superior à dos idosos sem DP, de forma significativa. Verificou-se melhoria significativa do tempo na realização do TUG, aumento do passo e da passada, quando se associa o estímulo auditivo à marcha, em idosos com ou sem a DP (0,027<p<0,028). Conclusão: A aplicação imediata de estímulos auditivos na marcha em idosos com e sem a DP tem um impacto positivo, melhorando o tempo e o comprimento do passo e da passada na marcha.Objective: To evaluate the immediate auditory cues on gait training in elderly people with and without Parkinson’s Disease (PD). Methodology: The study was composed by a sample of 6 elderly people with PD (77,67 ± 6,65 years; 25,58 ± 2,07 kg/m2) and 6 without PD (80 ± 7,46 years; 25,66 ± 1,18 kg/m2). The study consisted of applying the following tests in the 12 participants: United PD Rating Scale, Berg Balance Scale, cadence evaluation, and Timed Up and Go Test (TUG), this last test with or without auditory cues, analyzing the time, step length and stride during the gait. Results: Elderly people with PD have a higher cadence to the elderly without PD significantly. We can verify a significant increase of time in TUG and an increase of length in step and stride, when combining auditory cues to march in the elderly participants with or without PD (0,027<p<0,028). Conclusion: The immediate application of auditory cues in gait in elderly with or without PD has a positive effect, by increasing the cadence, the length of step and of stride