For an overview of the work from my research group,
please check this list of successfull PhD theses.
MOBILITY IN AGEING
My research aims are:
- to understand the effects of (biological) ageing on neuromuscular and cognitive aspects of mobility (i.e., physical function and physical activity)
- to implement this knowledge with assistive technology to maintain and promote mobility of older individuals in their own environment
The approaches for these aims are experimental studies (neuromuscular and biomechanical analyses), epidemiological studies (prediction models based on longitudinal cohort data), implementation of technological devices (e.g. accelerometry, kinect, smartphones, smartwatches) and interventions on fall prevention and active ageing in daily life behaviour.
CURRENT RESEARCH PROJECTS
- In Balans: the (cost-)effectiveness of a fall prevention intervention on falls and fall injuries in community-dwelling older adults with an increased risk of falls.
In project we to assess the (cost-)effectiveness of the falls prevention intervention ‘In Balans’, in community-dwelling older persons with an increased risk of falls, as compared to general exercise recommendations. We currently run a Randomized Clinical Trial in 256 participants accross the Netherlands. This ZonMw project is in a collaboration with Amsterdam University of Applied Sciences and VeiligheidNL. More information can be found here.
- The effect of exercise-induced fatigue on mobility and falls in non- and pre-frail older adults.
This research proposal focuses on the relationship between exercise-induced fatigue and the risk of falling amongst elderly, with special attention to one’s self-perceived capabilities. If elderly do not (sufficiently) perceive this fatigue, there is a risk that they do not respond adequately to balance disturbances, resulting in a fall. More info can be found here. - Applying AI in gait rehabilitation of stroke survivors
To optimize gait analysis as a diagnostic and evaluation tool in the clinical rehabilitation of patients with central neurological disorders this project aims to 1) develop an explainable AI approach to unravel the reasoning of the network and explain the participant’s gait pattern characteristics; 2) Compare to what extent these characteristics are also recognized in clinical gait analysis by a clinician 3) Investigate whether the diagnostic value of unsupervised artificial neural networks will improve the gait rehabilitation outcome.
PREVIOUS RESEARCH PROJECTS
- MOVITA: Wearable technology to optimize prognostic evaluation and rehabilitation of gait behaviour in orthopaedic patients
In MOVITA (Move, Visualise, Tailor), we develop a solution to remotely assess, store, and visualize an OA patient’s daily-life physical behaviour to monitor progression without costly hospital visits. Objective assessment and visualisation of daily-life physical behaviour and gait quality using new wearable technology will facilitate effectiveness in prognostics and treatment of these patients, while minimising required care and optimising patient satisfaction.
MOVITA is a collaborative initiative between the department Human Movement Sciences (Vrije Universiteit Amsterdam), two clinical departments of orthopaedics (Noordwest Ziekenhuisgroep and Sint Maartenskliniek) and two commercial partners (McRoberts B.V. and Moveshelf Labs B.V.), and sponsored by ZonMw and Health Holland. - REACT: advanced technology for perturbation-based treadmill training
This project, as part of the EU-ITN programme Keep Control, was aimed at the development and evaluation of a perturbation-based treadmill training intervention. We performed an RCT with 70 older adults and compared the effects of a 4-week perturbation training against unperturbed treadmill training on balance and gait performance, self-efficacy, physical activity and daily life gait quality. - Falls due to a mismatch between self-perceived and actual abilities in older adults
In my VIDI project we investigating the causes and consequences of misjudgements by older adults their biomechanical abilities in relation to biomechanical task requirements, by a combination of experimental studies and a prospective cohort study (VIBE: Veilig in Beweging Blijven). - PreventIT: Early risk detection and prevention of functional decline in young older adults with ICT support
In this project we developed a proof of concept of an unobtrusive mobile health system for young old people (60-70 years). This involves assessment for the risk for functional decline and eligibility for intervention. In a feasibility RCT, we integrated balance, strength and physical activity components in the daily life activities of our target group. For more information and outcomes, visit the PreventIT website. - Fall Risk Assessment in Older Adults (FARAO) based on accelerometry obtained during daily life activities
In the FARAO project we focused on predicting falls based on daily life gait characteristics obtained with one-week accelerometry data in a cohort of 300 older community-dwelling participants. We found that gait quality measures of daily life gait have added value to predicting falls. - Ability to respond to balance perturbations in young versus older adults
We studied the mechanics and control of recovery responses after balance perturbations during walking. For example, we developed a unique setup with 21 hidden obstacles to trip participants repeatedly during overground walking. We showed that the rate of force generation in the lower limbs during their recovery reaction discriminates older fallers from non-fallers and young adults. - Identification of high-risk fallers and targets for fall prevention training
We investigated whether fallers can be identified from results of muscle strength tests. Furthermore, we investigated the effect of strength training in a group of elderly on functional tasks as tripping. - MedioLateral Balance Assessement (MELBA)
We developed a new method to assess mediolateral balance performance using a visal tracking task. This tool was shown to be reliable, direction specific, challenging, and greater sensitivity to age than conventional balance measures. These features allow for identification of subtle balance impairments in older adults, which were predictive in instabilities in real-life gait.
