Arne Mueller
Overview
Explore the profile of Arne Mueller including associated specialties, affiliations and a list of published articles.
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Articles
20
Citations
277
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Recent Articles
1.
Kirk C, Kuderle A, Encarna Mico-Amigo M, Bonci T, Paraschiv-Ionescu A, Ullrich M, et al.
Sci Rep
. 2024 Nov;
14(1):28878.
PMID: 39572620
No abstract available.
2.
Encarna Mico-Amigo M, Bonci T, Paraschiv-Ionescu A, Ullrich M, Kirk C, Soltani A, et al.
J Neuroeng Rehabil
. 2024 May;
21(1):71.
PMID: 38702693
No abstract available.
3.
Kluge F, Brand Y, Encarna Mico-Amigo M, Bertuletti S, DAscanio I, Gazit E, et al.
JMIR Form Res
. 2024 May;
8:e50035.
PMID: 38691395
Background: Wrist-worn inertial sensors are used in digital health for evaluating mobility in real-world environments. Preceding the estimation of spatiotemporal gait parameters within long-term recordings, gait detection is an important...
4.
Kirk C, Kuderle A, Encarna Mico-Amigo M, Bonci T, Paraschiv-Ionescu A, Ullrich M, et al.
Sci Rep
. 2024 Jan;
14(1):1754.
PMID: 38243008
This study aimed to validate a wearable device's walking speed estimation pipeline, considering complexity, speed, and walking bout duration. The goal was to provide recommendations on the use of wearable...
5.
Buekers J, Megaritis D, Koch S, Alcock L, Ammour N, Becker C, et al.
ERJ Open Res
. 2023 Sep;
9(5).
PMID: 37753279
Background: Gait characteristics are important risk factors for falls, hospitalisations and mortality in older adults, but the impact of COPD on gait performance remains unclear. We aimed to identify differences...
6.
Encarna Mico-Amigo M, Bonci T, Paraschiv-Ionescu A, Ullrich M, Kirk C, Soltani A, et al.
J Neuroeng Rehabil
. 2023 Jun;
20(1):78.
PMID: 37316858
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...
7.
Salis F, Bertuletti S, Bonci T, Caruso M, Scott K, Alcock L, et al.
Front Bioeng Biotechnol
. 2023 May;
11:1143248.
PMID: 37214281
Accurately assessing people's gait, especially in real-world conditions and in case of impaired mobility, is still a challenge due to intrinsic and extrinsic factors resulting in gait complexity. To improve...
8.
Clay I, Peerenboom N, Connors D, Bourke S, Keogh A, Wac K, et al.
Digit Biomark
. 2023 May;
7(1):28-44.
PMID: 37206894
Background: Digital measures offer an unparalleled opportunity to create a more holistic picture of how people who are patients behave in their real-world environments, thereby establishing a better connection between...
9.
Scott K, Bonci T, Salis F, Alcock L, Buckley E, Gazit E, et al.
J Neuroeng Rehabil
. 2022 Dec;
19(1):141.
PMID: 36522646
Background: Measuring mobility in daily life entails dealing with confounding factors arising from multiple sources, including pathological characteristics, patient specific walking strategies, environment/context, and purpose of the task. The primary...
10.
Mazza C, Alcock L, Aminian K, Becker C, Bertuletti S, Bonci T, et al.
BMJ Open
. 2021 Dec;
11(12):e050785.
PMID: 34857567
Introduction: 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...