Binod Thapa-Chhetry

603 total citations
13 papers, 378 citations indexed

About

Binod Thapa-Chhetry is a scholar working on General Health Professions, Computer Vision and Pattern Recognition and Cognitive Neuroscience. According to data from OpenAlex, Binod Thapa-Chhetry has authored 13 papers receiving a total of 378 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in General Health Professions, 3 papers in Computer Vision and Pattern Recognition and 3 papers in Cognitive Neuroscience. Recurrent topics in Binod Thapa-Chhetry's work include Mobile Health and mHealth Applications (4 papers), Physical Activity and Health (3 papers) and Functional Brain Connectivity Studies (3 papers). Binod Thapa-Chhetry is often cited by papers focused on Mobile Health and mHealth Applications (4 papers), Physical Activity and Health (3 papers) and Functional Brain Connectivity Studies (3 papers). Binod Thapa-Chhetry collaborates with scholars based in United States and United Kingdom. Binod Thapa-Chhetry's co-authors include Stephen Intille, Christopher J. L. Newth, Junzi Dong, Ramin V. Parsey, J. John Mann, David Inwald, Ting Feng, Vinay Vaidya, María A. Oquendo and M. Elizabeth Sublette and has published in prestigious journals such as PLoS ONE, Medicine & Science in Sports & Exercise and Journal of Affective Disorders.

In The Last Decade

Binod Thapa-Chhetry

13 papers receiving 376 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Binod Thapa-Chhetry United States 9 115 94 55 50 47 13 378
Edgar Mesquita Portugal 7 169 1.5× 44 0.5× 18 0.3× 25 0.5× 14 0.3× 19 338
Jin Yeong Choe South Korea 8 81 0.7× 66 0.7× 174 3.2× 12 0.2× 31 0.7× 20 391
Maria Filippou-Frye United States 10 65 0.6× 60 0.6× 21 0.4× 7 0.1× 148 3.1× 16 459
Ching-Feng Huang Taiwan 13 86 0.7× 39 0.4× 144 2.6× 14 0.3× 18 0.4× 26 384
Khamis Abu‐Hasaballah United States 8 46 0.4× 54 0.6× 75 1.4× 4 0.1× 100 2.1× 12 387
Jan Johansson Sweden 14 52 0.5× 22 0.2× 21 0.4× 9 0.2× 103 2.2× 35 403
Tomasz Krauze Poland 15 108 0.9× 45 0.5× 10 0.2× 5 0.1× 40 0.9× 71 947
Zhi Zhou China 15 105 0.9× 40 0.4× 91 1.7× 3 0.1× 148 3.1× 47 679
Luiz Fernando Junqueira Brazil 19 81 0.7× 19 0.2× 20 0.4× 8 0.2× 290 6.2× 53 953
Mark Llewellyn Smith New Zealand 9 118 1.0× 8 0.1× 34 0.6× 42 0.8× 13 0.3× 18 460

Countries citing papers authored by Binod Thapa-Chhetry

Since Specialization
Citations

This map shows the geographic impact of Binod Thapa-Chhetry'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 Binod Thapa-Chhetry with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Binod Thapa-Chhetry more than expected).

Fields of papers citing papers by Binod Thapa-Chhetry

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Binod Thapa-Chhetry. 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 Binod Thapa-Chhetry. The network helps show where Binod Thapa-Chhetry may publish in the future.

Co-authorship network of co-authors of Binod Thapa-Chhetry

This figure shows the co-authorship network connecting the top 25 collaborators of Binod Thapa-Chhetry. A scholar is included among the top collaborators of Binod Thapa-Chhetry 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 Binod Thapa-Chhetry. Binod Thapa-Chhetry is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

13 of 13 papers shown
1.
Keadle, Sarah Kozey, Scott J. Strath, John R. Sirard, et al.. (2023). Evaluation of Within- and Between-Site Agreement for Direct Observation of Physical Behavior Across Four Research Groups. Journal for the Measurement of Physical Behaviour. 6(3). 176–184. 3 indexed citations
2.
Thapa-Chhetry, Binod, et al.. (2022). Detecting Sleep and Nonwear in 24-h Wrist Accelerometer Data from the National Health and Nutrition Examination Survey. Medicine & Science in Sports & Exercise. 54(11). 1936–1946. 9 indexed citations
3.
Ponnada, Aditya, Binod Thapa-Chhetry, Justin Manjourides, & Stephen Intille. (2021). Measuring Criterion Validity of Microinteraction Ecological Momentary Assessment (Micro-EMA): Exploratory Pilot Study With Physical Activity Measurement. JMIR mhealth and uhealth. 9(3). e23391–e23391. 22 indexed citations
4.
Dong, Junzi, Ting Feng, Binod Thapa-Chhetry, et al.. (2021). Machine learning model for early prediction of acute kidney injury (AKI) in pediatric critical care. Critical Care. 25(1). 288–288. 117 indexed citations
5.
Ponnada, Aditya, et al.. (2021). Signaligner Pro: A Tool to Explore and Annotate Multi-day Raw Accelerometer Data. PubMed. 2021. 475–480. 3 indexed citations
6.
John, Dinesh, et al.. (2020). Posture and Physical Activity Detection: Impact of Number of Sensors and Feature Type. Medicine & Science in Sports & Exercise. 52(8). 1834–1845. 13 indexed citations
7.
Amiri, Amir Mohammad, Binod Thapa-Chhetry, Margaret Finley, et al.. (2020). Relationship between pain, fatigue, and physical activity levels during a technology-based physical activity intervention. Journal of Spinal Cord Medicine. 44(4). 549–556. 9 indexed citations
8.
Hiremath, Shivayogi V., Amir Mohammad Amiri, Binod Thapa-Chhetry, et al.. (2019). Mobile health-based physical activity intervention for individuals with spinal cord injury in the community: A pilot study. PLoS ONE. 14(10). e0223762–e0223762. 30 indexed citations
9.
10.
Ponnada, Aditya, et al.. (2019). Designing Videogames to Crowdsource Accelerometer Data Annotation for Activity Recognition Research. PubMed. 2019. 135–147. 5 indexed citations
11.
Rubin‐Falcone, Harry, Francesca Zanderigo, Binod Thapa-Chhetry, et al.. (2017). Pattern recognition of magnetic resonance imaging-based gray matter volume measurements classifies bipolar disorder and major depressive disorder. Journal of Affective Disorders. 227. 498–505. 59 indexed citations
12.
Olvet, Doreen M., Denis Peruzzo, Binod Thapa-Chhetry, et al.. (2014). A diffusion tensor imaging study of suicide attempters. Journal of Psychiatric Research. 51. 60–67. 64 indexed citations
13.
DeLorenzo, Christine, et al.. (2013). Prediction of Selective Serotonin Reuptake Inhibitor Response Using Diffusion-Weighted MRI. Frontiers in Psychiatry. 4. 5–5. 41 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Edgar Mesquita Breakdown of academic impact, for papers by Jin Yeong Choe Breakdown of academic impact, for papers by Maria Filippou-Frye Breakdown of academic impact, for papers by Ching-Feng Huang Breakdown of academic impact, for papers by Khamis Abu‐Hasaballah Breakdown of academic impact, for papers by Jan Johansson Breakdown of academic impact, for papers by Tomasz Krauze Breakdown of academic impact, for papers by Zhi Zhou Breakdown of academic impact, for papers by Luiz Fernando Junqueira Breakdown of academic impact, for papers by Mark Llewellyn Smith
Rankless by CCL
2026