Lars Schwickert

668 total citations
18 papers, 494 citations indexed

About

Lars Schwickert is a scholar working on Physical Therapy, Sports Therapy and Rehabilitation, Computer Vision and Pattern Recognition and Biomedical Engineering. According to data from OpenAlex, Lars Schwickert has authored 18 papers receiving a total of 494 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Physical Therapy, Sports Therapy and Rehabilitation, 8 papers in Computer Vision and Pattern Recognition and 6 papers in Biomedical Engineering. Recurrent topics in Lars Schwickert's work include Balance, Gait, and Falls Prevention (11 papers), Context-Aware Activity Recognition Systems (8 papers) and Non-Invasive Vital Sign Monitoring (5 papers). Lars Schwickert is often cited by papers focused on Balance, Gait, and Falls Prevention (11 papers), Context-Aware Activity Recognition Systems (8 papers) and Non-Invasive Vital Sign Monitoring (5 papers). Lars Schwickert collaborates with scholars based in Germany, Italy and Norway. Lars Schwickert's co-authors include Jochen Klenk, Clemens Becker, Lorenzo Chiari, Jorunn L. Helbostad, Alan Bourke, Sabato Mellone, Kamiar Aminian, Ulrich Lindemann, Chris Todd and Wiebren Zijlstra and has published in prestigious journals such as PLoS ONE, Sensors and Journal of Medical Internet Research.

In The Last Decade

Lars Schwickert

18 papers receiving 484 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Lars Schwickert Germany 12 249 240 235 66 59 18 494
Carmen Abbott United States 14 229 0.9× 212 0.9× 260 1.1× 82 1.2× 52 0.9× 32 609
Carlo Tacconi Italy 10 165 0.7× 147 0.6× 186 0.8× 82 1.2× 41 0.7× 16 472
C. Becker Germany 7 361 1.4× 317 1.3× 270 1.1× 45 0.7× 22 0.4× 7 596
Inês Sousa Portugal 15 196 0.8× 206 0.9× 128 0.5× 52 0.8× 61 1.0× 51 574
Omar Aziz Canada 11 308 1.2× 283 1.2× 198 0.8× 28 0.4× 22 0.4× 27 543
Farzin Dadashi Switzerland 16 117 0.5× 331 1.4× 236 1.0× 68 1.0× 40 0.7× 28 696
Luca Palmerini Italy 18 263 1.1× 394 1.6× 533 2.3× 205 3.1× 58 1.0× 40 1.0k
Kejia Wang Australia 8 137 0.6× 124 0.5× 197 0.8× 53 0.8× 27 0.5× 8 365
S. Nicolai Germany 9 114 0.5× 144 0.6× 206 0.9× 97 1.5× 43 0.7× 17 402
Fabio Bagalà Italy 9 360 1.4× 304 1.3× 229 1.0× 28 0.4× 9 0.2× 12 504

Countries citing papers authored by Lars Schwickert

Since Specialization
Citations

This map shows the geographic impact of Lars Schwickert's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Lars Schwickert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lars Schwickert more than expected).

Fields of papers citing papers by Lars Schwickert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lars Schwickert. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Lars Schwickert. The network helps show where Lars Schwickert may publish in the future.

Co-authorship network of co-authors of Lars Schwickert

This figure shows the co-authorship network connecting the top 25 collaborators of Lars Schwickert. A scholar is included among the top collaborators of Lars Schwickert based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Lars Schwickert. Lars Schwickert is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
1.
Schwickert, Lars, et al.. (2020). Re-Enactment as a Method to Reproduce Real-World Fall Events Using Inertial Sensor Data: Development and Usability Study. Journal of Medical Internet Research. 22(4). e13961–e13961. 3 indexed citations
2.
Nerz, Corinna, Lars Schwickert, Stefan Studier-Fischer, et al.. (2020). Robot-assisted training after proximal humeral fracture: A randomised controlled multicentre intervention trial. Clinical Rehabilitation. 35(2). 242–252. 5 indexed citations
3.
Klenk, Jochen, et al.. (2019). Change of Objectively-Measured Physical Activity during Geriatric Rehabilitation. Sensors. 19(24). 5451–5451. 11 indexed citations
4.
5.
Klenk, Jochen, Clemens Becker, Pierpaolo Palumbo, et al.. (2017). Conceptualizing a Dynamic Fall Risk Model Including Intrinsic Risks and Exposures. Journal of the American Medical Directors Association. 18(11). 921–927. 37 indexed citations
6.
7.
Aziz, Omar, Jochen Klenk, Lars Schwickert, et al.. (2017). Validation of accuracy of SVM-based fall detection system using real-world fall and non-fall datasets. PLoS ONE. 12(7). e0180318–e0180318. 65 indexed citations
8.
Becker, Clemens, et al.. (2017). Inter-rater and intra-rater reliability of an adapted Wolf motor function test for older patients with shoulder injuries. Zeitschrift für Gerontologie und Geriatrie. 51(3). 293–300. 4 indexed citations
9.
Schwickert, Lars, et al.. (2016). Inertial Sensor Based Analysis of Lie-to-Stand Transfers in Younger and Older Adults. Sensors. 16(8). 1277–1277. 12 indexed citations
10.
Klenk, Jochen, Karin Srulijes, Cornelia Schatton, et al.. (2016). Ambulatory Activity Components Deteriorate Differently across Neurodegenerative Diseases: A Cross-Sectional Sensor-Based Study. Neurodegenerative Diseases. 16(5-6). 317–323. 10 indexed citations
11.
Bourke, Alan, Jochen Klenk, Lars Schwickert, et al.. (2016). Fall detection algorithms for real-world falls harvested from lumbar sensors in the elderly population: A machine learning approach. PubMed. 2016. 3712–3715. 33 indexed citations
12.
Schwickert, Lars, Ulrich Lindemann, Jochen Klenk, et al.. (2015). Model development to study strategies of younger and older adults getting up from the floor. Aging Clinical and Experimental Research. 28(2). 277–287. 11 indexed citations
13.
14.
Bourke, Alan, Jochen Klenk, Lars Schwickert, et al.. (2015). Temporal and kinematic variables for real-world falls harvested from lumbar sensors in the elderly population. PubMed. 2015. 5183–5186. 8 indexed citations
15.
Schwickert, Lars, C. Becker, Ulrich Lindemann, et al.. (2013). Fall detection with body-worn sensors. Zeitschrift für Gerontologie und Geriatrie. 46(8). 706–719. 115 indexed citations
16.
Mellone, Sabato, Carlo Tacconi, Lars Schwickert, et al.. (2012). Smartphone-based solutions for fall detection and prevention: the FARSEEING approach. Zeitschrift für Gerontologie und Geriatrie. 45(8). 722–727. 82 indexed citations
17.
Becker, Clemens, Lars Schwickert, Sabato Mellone, et al.. (2012). Proposal for a multiphase fall model based on real-world fall recordings with body-fixed sensors. Zeitschrift für Gerontologie und Geriatrie. 45(8). 707–715. 45 indexed citations
18.
Schwickert, Lars, et al.. (2011). Robotic-assisted rehabilitation of proximal humerus fractures in virtual environments. Zeitschrift für Gerontologie und Geriatrie. 44(6). 387–392. 18 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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