A5066284696- Balance, Gait, and Falls Prevention
- Cerebral Palsy and Movement Disorders
- Parkinson's Disease Mechanisms and Treatments
- Sports Performance and Training
- Muscle activation and electromyography studies
- Sports injuries and prevention
- Stroke Rehabilitation and Recovery
- Motor Control and Adaptation
- Diabetic Foot Ulcer Assessment and Management
- Gait Recognition and Analysis
- Musculoskeletal pain and rehabilitation
- Chronic Obstructive Pulmonary Disease (COPD) Research
- Context-Aware Activity Recognition Systems
- Neurological disorders and treatments
- Shoulder Injury and Treatment
- Restless Legs Syndrome Research
- Cardiovascular and exercise physiology
- Winter Sports Injuries and Performance
- Inertial Sensor and Navigation
- Non-Invasive Vital Sign Monitoring
- Effects of Vibration on Health
- Lower Extremity Biomechanics and Pathologies
- Robot Manipulation and Learning
- Prosthetics and Rehabilitation Robotics
- Assistive Technology in Communication and Mobility
Kiel University
2016-2025
University Hospital Schleswig-Holstein
2017-2025
University of Lübeck
2017-2025
Université Grenoble Alpes
2024
Agence Régionale de Santé Ile-de-France
2023-2024
University Medical Center
2022
University Hospital and Clinics
2022
Hertie Institute for Clinical Brain Research
2022
University of Tübingen
2022
Universitäts Hautklinik Kiel
2020
Quantification of gait with wearable technology is promising; recent cross-sectional studies showed that characteristics are potential prodromal markers for Parkinson disease (PD). The aim this longitudinal prospective observational study was to establish impairments and trajectories in the phase PD, identifying which potentially early diagnostic PD.The 696 healthy controls (mean age = 63 ± 7 years) recruited Tubingen Evaluation Risk Factors Early Detection Neurodegeneration were included....
Abstract Background Although digital mobility outcomes (DMOs) can be readily calculated from real-world data collected with wearable devices and ad-hoc algorithms, technical validation is still required. The aim of this paper to comparatively assess validate DMOs estimated using gait six different cohorts, focusing on sequence detection, foot initial contact detection (ICD), cadence (CAD) stride length (SL) estimates. Methods Twenty healthy older adults, 20 people Parkinson’s disease,...
Abstract This study aimed to validate a wearable device’s walking speed estimation pipeline, considering complexity, speed, and bout duration. The goal was provide recommendations on the use of devices for real-world mobility analysis. Participants with Parkinson’s Disease, Multiple Sclerosis, Proximal Femoral Fracture, Chronic Obstructive Pulmonary Congestive Heart Failure, healthy older adults (n = 97) were monitored in laboratory (2.5 h), using lower back device. Two pipelines validated...
Inertial measurement units (IMUs) positioned on various body locations allow detailed gait analysis even under unconstrained conditions. From a medical perspective, the assessment of vulnerable populations is particular relevance, especially in daily-life environment. Gait algorithms need thorough validation, as many chronic diseases show specific and unique patterns. The aim this study was therefore to validate an acceleration-based step detection algorithm for patients with Parkinson's...
Existing mobility endpoints based on functional performance, physical assessments and patient self-reporting are often affected by lack of sensitivity, limiting their utility in clinical practice. Wearable devices including inertial measurement units (IMUs) can overcome these limitations quantifying digital outcomes (DMOs) both during supervised structured real-world conditions. The validity IMU-based methods the real-world, however, is still limited populations. Rigorous validation...
Abstract Physical mobility is essential to health, and patients often rate it as a high-priority clinical outcome. Digital outcomes (DMOs), such real-world gait speed or step count, show promise measures in many medical conditions. However, current research nascent fragmented by discipline. This scoping review maps existing evidence on the utility of DMOs, identifying commonalities across traditional disciplinary divides. In November 2019, 11 databases were searched for records investigating...
Abstract Background Identification of individual gait events is essential for clinical analysis, because it can be used diagnostic purposes or tracking disease progression in neurological diseases such as Parkinson’s disease. Previous research has shown that detected from a shank-mounted inertial measurement unit (IMU), however detection performance was often evaluated only straight-line walking. For use daily life, the needs to curved walking and turning well single-task dual-task...
Many algorithms use 3D accelerometer and/or gyroscope data from inertial measurement unit (IMU) sensors to detect gait events (i.e., initial and final foot contact). However, these often require knowledge about sensor orientation empirically derived thresholds. As alignment cannot always be controlled for in ambulatory assessments, methods are needed that little on location orientation, e.g., a convolutional neural network-based deep learning model. Therefore, 157 participants healthy...
Background This study aimed to explore the acceptability of a wearable device for remotely measuring mobility in Mobilise-D technical validation (TVS), and using digital tools monitor health. Methods Participants ( N = 106) TVS wore waist-worn (McRoberts Dynaport MM + ) one week. Following this, was measured two questionnaires: The Comfort Rating Scale (CRS) previously validated questionnaire. A subset participants n 36) also completed semi-structured interviews further determine their...
Introduction: Accurately assessing people’s gait, especially in real-world conditions and case of impaired mobility, is still a challenge due to intrinsic extrinsic factors resulting gait complexity. To improve the estimation gait-related digital mobility outcomes (DMOs) scenarios, this study presents wearable multi-sensor system (INDIP), integrating complementary sensing approaches (two plantar pressure insoles, three inertial units two distance sensors). Methods: The INDIP technical...
Abstract Wearable devices are used in movement analysis and physical activity research to extract clinically relevant information about an individual’s mobility. Still, heterogeneity protocols, sensor characteristics, data formats, gold standards represent a barrier for sharing, reproducibility, external validation. In this study, we aim at providing example of how (from the real-world laboratory) recorded from different wearables standard technologies can be organized, integrated, stored....
Background Wrist-worn inertial sensors are used in digital health for evaluating mobility real-world environments. Preceding the estimation of spatiotemporal gait parameters within long-term recordings, detection is an important step to identify regions interest where occurs, which requires robust algorithms due complexity arm movements. While exist other sensor positions, a comparative validation applied wrist position on data sets across different disease populations missing. Furthermore,...
Abstract Fatigue is prevalent in immune-mediated inflammatory and neurodegenerative diseases, yet its assessment relies largely on patient-reported outcomes, which capture perception but not fluctuations over time. Wearable sensors, like inertial measurement units (IMUs), offer a way to monitor daily activities evaluate functional capacity. This study investigates the relationship between sit-to-stand stand-to-sit transitions self-reported physical mental fatigue participants with...
The present study aimed to compare various entropy measures assess the dynamics and complexity of center pressure (COP) displacements. Perturbing balance tests are often used in healthy subjects imitate either pathological conditions or test sensitivity postural analysis techniques. Eleven adult were asked stand normal stance three experimental while visuo-kinesthetic input was altered. COP displacement recorded using a force plate. Three [Sample Entropy (SE), Multi-Scale (MSE), Multivariate...
Use of a commercially available wearable device to monitor jump load with elite volleyball players has become common practice. The purpose this study was evaluate the validity and reliability device, Vert, count jumps measure height professional players. Jump accuracy determined by comparing recorded observed through systematic video analysis three practice sessions two league matches performed men's team. Jumps 14 were each coded for time type individually matched jumps. examined against...
Abstract Prevalence of gait impairments increases with age and is associated mobility decline, fall risk loss independence. For geriatric patients, the having disorders even higher. Consequently, assessment in clinics has become increasingly important. The purpose present study was to classify healthy young-middle aged, older adults patients based on dynamic outcomes. Classification performance three supervised machine learning methods compared. From trunk 3D-accelerations 239 subjects...
Digital mobility assessment using wearable sensor systems has the potential to capture walking performance in a patient’s natural environment. It enables monitoring of health status and disease progression evaluation interventions real-world situations. In contrast laboratory settings, occurs non-conventional environments under unconstrained uncontrolled conditions. Despite general understanding, there is lack agreed definitions about what constitutes walking, impeding comparison...
Peripheral neuropathy is a common problem in patients with Parkinson's disease. neuropathy's prevalence disease varies between 4.8-55%, compared 9% the general population. It remains unclear whether peripheral leads to decreased motor performance disease, resulting impaired mobility and increased balance deficits. We aimed determine type of evaluate its functional impact on gait balance. A cohort consecutive assessed by movement disorders specialists based UK Brain Bank criteria underwent...
We present an extension to the Brain Imaging Data Structure (BIDS) for motion data. Motion data is frequently recorded alongside human brain imaging and electrophysiological The goal of Motion-BIDS make interoperable across different laboratories with other modalities in behavioral research. To this end, standardizes format metadata structure. It describes how document experimental details, considering diversity hardware software systems This promotes findable, accessible, interoperable,...
Deficits in gait and balance are common among neurological inpatients. Currently, assessment of these patients is mainly subjective. New options using wearables may provide complementary more objective information.In this prospective cross-sectional feasibility study performed over a four-month period, all referred to normal neurology ward university hospital aged between 40 89 years were asked participate. Gait deficits assessed with at the ankles lower back. Frailty, sarcopenia,...
Aim To investigate the association of daily clinical measures and progression rehabilitation perceived running effort. Methods A cohort 131 athletes with an MRI-confirmed acute hamstring injury underwent a standardised criteria-based protocol. Descriptive inferential statistics were used to between subjective objective both These included different strength, palpation, flexibility functional tests. Inter-rater intrarater reliability minimal detectable change established for strength by...
Falls are the leading cause of mortality, morbidity and poor quality life in older adults with or without neurological conditions. Applying machine learning (ML) models to gait analysis outcomes offers opportunity identify individuals at risk future falls. The aim this study was determine effect different data pre-processing methods on performance ML classify patients who have fallen from those not for fall assessment. Gait assessed using wearables clinic while walking 20 m a self-selected...
Abstract Background Human well-being has been linked to the composition and functional capacity of intestinal microbiota. As regular exercise is known improve human health, it not surprising that was previously described positively modulate gut microbiota, too. However, most previous studies mainly focused on either elite athletes or animal models. Thus, we conducted a randomised intervention study effects different types training (endurance strength) in physically inactive, healthy adults...