BackgroundA key factor in successfully preventing falls, is early identification of elderly with a high risk of falling. However, currently there is no easy-to-use pre-screening tool available; current tools are either not discriminative, time-consuming and/or costly. This pilot investigates the feasibility of developing an automatic gait-screening method by using a low-cost optical sensor and machinelearning algorithms to automatically detect features and classify gait patterns.MethodParticipants (n = 204, age 27 ± 7 yrs.) performed a gait test under two conditions: control and with distorted depth perception (induced by wearing special goggles). Each test consisted of 4x 3m walking at comfortable speed. Full-body 3D kinematics were captured using an optical sensor (Microsoft Xbox One Kinect). Tests were conducted in a public space to establish relatively 'natural' conditions. Data was processed in Matlab and common spatiotemporal variables were calculated per gait section. The 3D-time series data of the centre of mass for each section was used as input for a neural network, that was trained to discriminate between the two conditions.ResultsWearing the goggles affected the gait pattern significantly: gait velocity and step length decreased, and lateral sway increased compared to the control condition. A 2-layer neural network could correctly classify 79% of the gait segments (i.e. with or without distorted vision).ConclusionsThe results show that gait patterns of healthy people with distorted vision could automatically be classified with the proposed approach. Future work will focus on adapting this model for identification of specific physical risk-factors in elderly.
Background: The diagnosis of sarcopenia is essential for early treatment of sarcopenia in older adults, for which assessment of appendicular lean mass (ALM) is needed. Multi-frequency bio-electrical impedance analysis (MF-BIA) may be a valid assessment tool to assess ALM in older adults, but the evidences are limited. Therefore, we validated the BIA to diagnose low ALM in older adults.Methods: ALM was assessed by a standing-posture 8 electrode MF-BIA (Tanita MC-780) in 202 community-dwelling older adults (age ≥ 55 years), and compared with dual-energy X-ray absorptiometry (DXA) (Hologic Inc., Marlborough, MA, United States; DXA). The validity for assessing the absolute values of ALM was evaluated by: (1) bias (mean difference), (2) percentage of accurate predictions (within 5% of DXA values), (3) the mean absolute error (MAE), and (4) limits of agreement (Bland-Altman analysis). The lowest quintile of ALM by DXA was used as proxy for low ALM (< 22.8 kg for men, < 16.1 kg for women). Sensitivity and specificity of diagnosing low ALM by BIA were assessed.Results: The mean age of the subjects was 72.1 ± 6.4 years, with a BMI of 25.4 ± 3.6 kg/m2, and 71% were women. BIA slightly underestimated ALM compared to DXA with a mean bias of -0.6 ± 1.2 kg. The percentage of accurate predictions was 54% with a MAE of 1.1 kg, and limits of agreement were -3.0 to + 1.8 kg. The sensitivity for ALM was 80%, indicating that 80% of subjects who were diagnosed as low ALM according to DXA were also diagnosed low ALM by BIA. The specificity was 90%, indicating that 90% of subjects who were diagnosed as normal ALM by DXA were also diagnosed as normal ALM by the BIA.Conclusion: This comparison showed a poor validity of MF-BIA to assess the absolute values of ALM, but a reasonable sensitivity and specificity to recognize the community-dwelling older adults with the lowest muscle mass.
Theme: Quality Assurance in Higher Education An online tool was developed for (potential) students to assess the congruence between the characteristics of an educational program and student preferences (Butter & Van Raalten, 2010)
De aanvraag betreft het ontwikkelen en verkennen van de marktmogelijkheden van een IT-tool dat de slaagkans van bedrijfsoverdrachten verbetert. De (emotionele) barrières die ondernemers bij de verkoop hun bedrijf tegenko-men worden inzichtelijk gemaakt. Tevens wordt getoetst of de manier waarop ondernemers nu omgaan met die barrières (coping) effectief is. De doelgroep voor het onderzoek zijn overname-adviseurs, kopende en verkopende ondernemers alsmede investeerders.
Project investigating the climate risk exposure of tourism destinations to develop a climate risk assessment methodology and tools for tourism destinations to manage climate risks.
Democratie, burgerschapsvorming, kritisch denken en Bildung worden vaak samen genoemd, maar een heldere kijk op de onderlinge samenhang ontbreekt nog. In dit onderzoeksproject ontwikkelen we een visie op burgerschapsvorming in het middelbaar beroepsonderwijs, waarin kritisch denken en Bildung worden opgenomen.Doel We willen met het project 'Democratisering van kritisch denken' de volgende doelen bereiken: Het formuleren van een heldere kijk op het samenbrengen van kritisch denken, burgerschap, Bildung en de beroepsvoorbereiding in het mbo; Het creëren van een duurzame, professionele leergemeenschap; De ontwikkeling van kennis om kritisch denken toe te passen in de lespraktijk; Het beschikbaar stellen van leerplannen en meetinstrumenten voor mbo-docenten. Resultaten Dit onderzoek loopt. Na afloop vind je hier een samenvatting van de resultaten. Looptijd 17 september 2018 - 31 januari 2023 Aanpak Dit project is onderdeel van de Werkplaats Onderwijsonderzoek van NRO. Deze werkplaatsen zijn gericht op het instellen van duurzame ‘professionele leergemeenschappen’. Ook in dit project komen verschillende expertises samen: die van mbo-docenten (Nederlands, Burgerschap en vakdocenten), onderzoekers van een practoraat, het Expertisecentrum Kritisch Denken (ECKD), het lectoraat Normatieve professionalisering en twee universiteiten. Studenten en externe partners brengen bovendien praktijkkennis in. Samen werken de partners aan een visie op kritisch denken, burgerschap en bildung en de vertaling hiervan in leerlijnen en assessment-tools. Samen met mbo-docenten kijken we bovendien welke professionalisering er nodig is om kritisch denken toe te passen in het beroepsonderwijs. Lees meer over het project Democratisering van kritisch denken.
