Michael Mace

822 total citations
30 papers, 501 citations indexed

About

Michael Mace is a scholar working on Cognitive Neuroscience, Biomedical Engineering and Neurology. According to data from OpenAlex, Michael Mace has authored 30 papers receiving a total of 501 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Cognitive Neuroscience, 11 papers in Biomedical Engineering and 7 papers in Neurology. Recurrent topics in Michael Mace's work include Muscle activation and electromyography studies (8 papers), Stroke Rehabilitation and Recovery (7 papers) and Speech and Audio Processing (7 papers). Michael Mace is often cited by papers focused on Muscle activation and electromyography studies (8 papers), Stroke Rehabilitation and Recovery (7 papers) and Speech and Audio Processing (7 papers). Michael Mace collaborates with scholars based in United Kingdom, United States and Singapore. Michael Mace's co-authors include Joel West, Etienne Burdet, Paul Bentley, Paul Rinne, Ravi Vaidyanathan, Anthony A. Rayner, Nawal Kinany, Shouyan Wang, Khondaker A. Mamun and Lalit Gupta and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Michael Mace

29 papers receiving 473 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Michael Mace United Kingdom	11	136	104	99	98	76	30	501
Kevin C. Tseng Taiwan	15	95 0.7×	88 0.8×	60 0.6×	13 0.1×	17 0.2×	44	601
Georgi V. Georgiev Finland	15	82 0.6×	29 0.3×	49 0.5×	20 0.2×	11 0.1×	102	730
Kostas Nizamis Netherlands	11	82 0.6×	246 2.4×	179 1.8×	4 0.0×	40 0.5×	29	436
Sangin Park South Korea	15	271 2.0×	219 2.1×	3 0.0×	100 1.0×	27 0.4×	59	839
Roberto Pérez‐Rodríguez Cuba	12	49 0.4×	38 0.4×	31 0.3×	30 0.3×	10 0.1×	53	464
Mark N. Gasson United Kingdom	13	262 1.9×	166 1.6×	16 0.2×	4 0.0×	99 1.3×	26	570
Sofia B. Dias Portugal	14	48 0.4×	62 0.6×	19 0.2×	3 0.0×	59 0.8×	52	633
Andrew Gorman United States	14	55 0.4×	57 0.5×	16 0.2×	14 0.1×	3 0.0×	37	993
Roseli de Deus Lopes Brazil	13	130 1.0×	48 0.5×	89 0.9×	5 0.1×	9 0.1×	131	737
Vijayakumar Nanjappan Finland	12	108 0.8×	25 0.2×	39 0.4×	5 0.1×	11 0.1×	41	492

Countries citing papers authored by Michael Mace

Since Specialization

Citations

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

Fields of papers citing papers by Michael Mace

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael Mace. 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 Michael Mace. The network helps show where Michael Mace may publish in the future.

Co-authorship network of co-authors of Michael Mace

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

All Works

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20 of 20 papers shown

Sharma, Deepika, et al.. (2024). GripAble: Interrater reliability and normative grip strength of UK population. Journal of Hand Therapy. 38(2). 397–408. 2 indexed citations

Mace, Michael, et al.. (2022). GripAble: An accurate, sensitive and robust digital device for measuring grip strength. Journal of Rehabilitation and Assistive Technologies Engineering. 9. 3374780855–3374780855. 9 indexed citations

Mace, Michael, et al.. (2022). Modernising grip dynamometry: Inter-instrument reliability between GripAble and Jamar. BMC Musculoskeletal Disorders. 23(1). 80–80. 15 indexed citations

Mace, Michael, et al.. (2019). Bimanual coordination during a physically coupled task in unilateral spastic cerebral palsy children. Journal of NeuroEngineering and Rehabilitation. 16(1). 1–1. 51 indexed citations

Mehring, Carsten, Michel Akselrod, Luke Bashford, et al.. (2019). Augmented manipulation ability in humans with six-fingered hands. Nature Communications. 10(1). 2401–2401. 40 indexed citations

Mace, Michael, Nawal Kinany, Paul Rinne, et al.. (2017). Balancing the playing field: collaborative gaming for physical training. Journal of NeuroEngineering and Rehabilitation. 14(1). 116–116. 47 indexed citations

Mace, Michael, et al.. (2017). Elasticity improves handgrip performance and user experience during visuomotor control. Royal Society Open Science. 4(2). 160961–160961. 15 indexed citations

Yousif, Nada, Michael Mace, Nicola Pavese, et al.. (2017). A Network Model of Local Field Potential Activity in Essential Tremor and the Impact of Deep Brain Stimulation. PLoS Computational Biology. 13(1). e1005326–e1005326. 20 indexed citations

Mace, Michael, Amir Hussain, E. Diane Playford, et al.. (2017). Validity of a sensor-based table-top platform to measure upper limb function. PubMed. 9. 652–657. 2 indexed citations

10.

Rinne, Paul, Michael Mace, Karl Zimmerman, et al.. (2016). Democratizing Neurorehabilitation: How Accessible are Low-Cost Mobile-Gaming Technologies for Self-Rehabilitation of Arm Disability in Stroke?. PLoS ONE. 11(10). e0163413–e0163413. 24 indexed citations

11.

Mamun, Khondaker A., Michael Mace, M.E. Lutman, et al.. (2015). Movement decoding using neural synchronization and inter-hemispheric connectivity from deep brain local field potentials. Journal of Neural Engineering. 12(5). 56011–56011. 27 indexed citations

12.

Mace, Michael, et al.. (2013). An automated approach towards detecting complex behaviours in deep brain oscillations. Journal of Neuroscience Methods. 224. 66–78. 6 indexed citations

13.

Mace, Michael, et al.. (2013). A heterogeneous framework for real-time decoding of bioacoustic signals: Applications to assistive interfaces and prosthesis control. Expert Systems with Applications. 40(13). 5049–5060. 10 indexed citations

14.

Mace, Michael, et al.. (2011). Ensemble classification for robust discrimination of multi-channel, multi-class tongue-movement ear pressure signals. PubMed. 2011. 1733–1736. 6 indexed citations

15.

Mamun, Khondaker A., Michael Mace, Lalit Gupta, et al.. (2011). Robust real-time identification of tongue movement commands from interferences. Neurocomputing. 80. 83–92. 6 indexed citations

16.

Mamun, Khondaker A., et al.. (2010). Multi-layer neural network classification of tongue movement ear pressure signal for human machine interface. 430–435. 1 indexed citations

17.

Mamun, Khondaker A., et al.. (2009). Bayesian classification of tongue movement based on wavelet packet transformation. ePrints Soton (University of Southampton). 2 indexed citations

18.

Mamun, K. A., et al.. (2009). Pattern classification of tongue movement ear pressure signal based on wavelet packet feature extraction. ePrints Soton (University of Southampton). 4 indexed citations

19.

Mamun, Khondaker A., et al.. (2009). Tongue movement ear pressure signal classification using wavelet packet transform. ePrints Soton (University of Southampton). 1 indexed citations

20.

Mace, Michael, Ghislaine Richard, Simon J. Thorpe, & M. Fabre‐Thorpe. (2003). Category-level hierarchy: what comes first in vision?. Acta Neurobiologiae Experimentalis. 63(5). 1 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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