Leveraging deep feature learning for wearable sensors based handwritten character recognition

Despite rapid advancements in technology, handwritten characters still hold significant roles in various fields, including education, communication, biometric signature verification, and health care. These applications often require digitization of the handwritten characters and associated hand move...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Biomedical signal processing and control Jg. 80; S. 104198
Hauptverfasser: Singh, Shashank Kumar, Chaturvedi, Amrita
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Ltd 01.02.2023
Schlagworte:
ISSN:1746-8094, 1746-8108
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Abstract Despite rapid advancements in technology, handwritten characters still hold significant roles in various fields, including education, communication, biometric signature verification, and health care. These applications often require digitization of the handwritten characters and associated hand movements to facilitate effective analysis and interpretation of the underlying task. Offline and online handwriting recognition are crucial steps involving the digitization of handwritten characters. Most of these existing systems actively use image processing techniques that are highly sensitive to environmental lighting conditions. Surface Electromyography signals (sEMG), being invariant to lighting conditions, are used in online handwriting recognition to facilitate the automatic transcription of handwritten characters. In this article, we have leveraged deep representation learning to build an efficient and robust sEMG-based Handwritten Character Recognition (HCR) pipeline. A Stacked sparse denoising autoencoder network is applied to obtain an effective deep feature representation. These rich low dimensional features obtained are further introduced into basic classifiers, producing state-of-the-art accuracy for the task. Additional experiments were performed to analyze the effect of the fusion of complementary sensing modules (Accelerometer and Gyroscope) on the performance of sEMG based HCR pipeline. Extensive evaluations were performed to ensure the validity of the obtained results. For the experimentation, new datasets consisting of sEMG, Accelerometer, and Gyroscope signals corresponding to 26 handwritten lower English alphabets were collected from 15 subjects. Our proposed pipeline can be used to build real-time Human–Computer Interaction(HCI) applications for smart classrooms facilitating digitization of handwritten notes and clinical applications involving handwriting analysis tasks. •We explored autoencoders for handwritten characters recognition using sEMG signals.•We recorded sEMG signals of 15 subjects while writing 26 lowercase English alphabets.•Deep stacked sparse denoising autoencoders were applied on this new dataset.•Further experimental analysis was done by coupling sEMG with IMU sensor module.•Our proposed approach achieved an accuracy of 98.72% even with baseline classifiers.•Our model can potentially be used in smart-classrooms and clinical applications.
AbstractList Despite rapid advancements in technology, handwritten characters still hold significant roles in various fields, including education, communication, biometric signature verification, and health care. These applications often require digitization of the handwritten characters and associated hand movements to facilitate effective analysis and interpretation of the underlying task. Offline and online handwriting recognition are crucial steps involving the digitization of handwritten characters. Most of these existing systems actively use image processing techniques that are highly sensitive to environmental lighting conditions. Surface Electromyography signals (sEMG), being invariant to lighting conditions, are used in online handwriting recognition to facilitate the automatic transcription of handwritten characters. In this article, we have leveraged deep representation learning to build an efficient and robust sEMG-based Handwritten Character Recognition (HCR) pipeline. A Stacked sparse denoising autoencoder network is applied to obtain an effective deep feature representation. These rich low dimensional features obtained are further introduced into basic classifiers, producing state-of-the-art accuracy for the task. Additional experiments were performed to analyze the effect of the fusion of complementary sensing modules (Accelerometer and Gyroscope) on the performance of sEMG based HCR pipeline. Extensive evaluations were performed to ensure the validity of the obtained results. For the experimentation, new datasets consisting of sEMG, Accelerometer, and Gyroscope signals corresponding to 26 handwritten lower English alphabets were collected from 15 subjects. Our proposed pipeline can be used to build real-time Human–Computer Interaction(HCI) applications for smart classrooms facilitating digitization of handwritten notes and clinical applications involving handwriting analysis tasks. •We explored autoencoders for handwritten characters recognition using sEMG signals.•We recorded sEMG signals of 15 subjects while writing 26 lowercase English alphabets.•Deep stacked sparse denoising autoencoders were applied on this new dataset.•Further experimental analysis was done by coupling sEMG with IMU sensor module.•Our proposed approach achieved an accuracy of 98.72% even with baseline classifiers.•Our model can potentially be used in smart-classrooms and clinical applications.
ArticleNumber 104198
Author Chaturvedi, Amrita
Singh, Shashank Kumar
Author_xml – sequence: 1
  givenname: Shashank Kumar
  surname: Singh
  fullname: Singh, Shashank Kumar
  email: shashankkrs.cse17@itbhu.ac.in
– sequence: 2
  givenname: Amrita
  orcidid: 0000-0002-3345-5103
  surname: Chaturvedi
  fullname: Chaturvedi, Amrita
  email: amrita.cse@iitbhu.ac.in
BookMark eNp9kE1LAzEQhoNUsK3-AU_5A62TzbpNwIsUv6DgRY8SkuykTVmzJYkt_nuzVC8eepqZl3nm452QUegDEnLNYM6ANTfbuUk7O6-gqopQMynOyJgt6mYmGIjRXw6yviCTlLYAtViwekw-VrjHqNc-rGmLuKMOdf6KSDvUMQyq6yM9lEKbDmnCkPqYqNEJW7rRoT1EnzMGajelxWaMNKLt18Fn34dLcu50l_DqN07J--PD2_J5tnp9elner2aWA-SZqZqqLGcITlhu0TWSNw0YLQ00kknmuC4X3_JWSL0w4Dgyq0UrpZFgBedTIo5zbexTiuiU9VkPF-SofacYqMEmtVWDTWqwSR1tKmj1D91F_6nj92no7ghheWrvMapkPQaLrS_fZ9X2_hT-AxnMhZc
CitedBy_id crossref_primary_10_1109_ACCESS_2023_3310819
crossref_primary_10_1016_j_bspc_2024_106910
crossref_primary_10_1145_3700143
crossref_primary_10_1002_adsr_202300118
crossref_primary_10_1109_JIOT_2024_3507369
crossref_primary_10_1155_2023_6897719
crossref_primary_10_1016_j_engappai_2024_109225
crossref_primary_10_1016_j_asoc_2024_111813
crossref_primary_10_3390_bioengineering11050458
crossref_primary_10_3389_fpls_2023_1177114
crossref_primary_10_1016_j_cmpb_2025_108908
crossref_primary_10_1109_TIM_2023_3327490
crossref_primary_10_1109_JSEN_2023_3265811
Cites_doi 10.1007/s11042-018-6293-x
10.1002/advs.202100711
10.1109/TNNLS.2020.2978386
10.1186/s12864-019-6413-7
10.1016/j.cmpb.2014.08.007
10.1007/s13369-020-05044-x
10.1109/34.824821
10.1109/RBME.2019.2950897
10.1007/s00422-015-0670-6
10.1109/TNSRE.2017.2687761
10.1145/3411842
10.1145/3458864.3467885
10.1016/j.bspc.2019.101733
10.1016/j.bspc.2020.101981
10.1016/S0167-9457(99)00028-7
10.1016/j.bspc.2022.103697
10.1016/j.patcog.2018.04.012
10.1109/TBCAS.2020.3005148
10.1016/j.bspc.2020.102074
10.3389/fnbot.2016.00015
10.1016/0031-3203(89)90059-9
10.1103/PhysRevE.55.5443
10.1007/s10618-013-0312-3
10.1145/2836041.2836063
10.3389/fnins.2015.00389
10.1159/000068484
10.1177/002221948501800406
10.1109/TIE.2011.2167895
10.1088/1741-2560/11/5/051001
10.1126/science.1127647
10.1007/s00702-005-0346-9
10.3390/s19204596
10.1109/TBME.2006.883696
10.1145/3173574.3173705
10.1177/0309364615605373
10.1098/rsta.2008.0235
10.1016/j.rasd.2012.12.004
10.1251/bpo124
10.1007/s00422-008-0278-1
10.1016/S0375-9601(00)00334-0
10.1109/JIOT.2019.2947448
10.1016/B978-0-12-821350-6.00006-8
10.11591/ijece.v8i6.pp4221-4229
10.1109/TSMCA.2011.2116004
10.1371/journal.pone.0006791
10.3390/app8071126
10.1186/s12984-018-0363-1
10.3934/mbe.2020293
10.1152/jappl.1986.60.4.1179
10.26599/TST.2021.9010017
10.1016/j.artmed.2016.01.004
ContentType Journal Article
Copyright 2022 Elsevier Ltd
Copyright_xml – notice: 2022 Elsevier Ltd
DBID AAYXX
CITATION
DOI 10.1016/j.bspc.2022.104198
DatabaseName CrossRef
DatabaseTitle CrossRef
DatabaseTitleList
DeliveryMethod fulltext_linktorsrc
Discipline Engineering
EISSN 1746-8108
ExternalDocumentID 10_1016_j_bspc_2022_104198
S1746809422006528
GroupedDBID ---
--K
--M
.~1
0R~
1B1
1~.
1~5
23N
4.4
457
4G.
5GY
5VS
6J9
7-5
71M
8P~
AACTN
AAEDT
AAEDW
AAIAV
AAIKJ
AAKOC
AALRI
AAOAW
AAQFI
AAXUO
AAYFN
ABBOA
ABFNM
ABFRF
ABJNI
ABMAC
ABXDB
ABYKQ
ACDAQ
ACGFO
ACGFS
ACNNM
ACRLP
ACZNC
ADBBV
ADEZE
ADMUD
ADTZH
AEBSH
AECPX
AEFWE
AEKER
AENEX
AFKWA
AFTJW
AGHFR
AGUBO
AGYEJ
AHJVU
AHZHX
AIALX
AIEXJ
AIKHN
AITUG
AJBFU
AJOXV
ALMA_UNASSIGNED_HOLDINGS
AMFUW
AMRAJ
AOUOD
AXJTR
BJAXD
BKOJK
BLXMC
CS3
DU5
EBS
EFJIC
EFLBG
EJD
EO8
EO9
EP2
EP3
F5P
FDB
FIRID
FNPLU
FYGXN
G-Q
GBLVA
GBOLZ
HZ~
IHE
J1W
JJJVA
KOM
M41
MO0
N9A
O-L
O9-
OAUVE
OZT
P-8
P-9
P2P
PC.
Q38
RIG
ROL
RPZ
SDF
SDG
SES
SPC
SPCBC
SST
SSV
SSZ
T5K
UNMZH
~G-
9DU
AATTM
AAXKI
AAYWO
AAYXX
ABWVN
ACLOT
ACRPL
ACVFH
ADCNI
ADNMO
AEIPS
AEUPX
AFJKZ
AFPUW
AIGII
AIIUN
AKBMS
AKRWK
AKYEP
ANKPU
APXCP
CITATION
EFKBS
~HD
ID FETCH-LOGICAL-c300t-b262dee1e0f8c3cef693660ba9b069191f3a00453d89a7b0f3e1ca8d99b90c833
ISICitedReferencesCount 18
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000875634300007&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN 1746-8094
IngestDate Sat Nov 29 07:02:06 EST 2025
Tue Nov 18 22:25:28 EST 2025
Fri Feb 23 02:38:47 EST 2024
IsPeerReviewed true
IsScholarly true
Keywords Accelerometers
Deep learning
Electromyogram
Gyroscopes
Biomedical signal processing
Language English
LinkModel OpenURL
MergedId FETCHMERGED-LOGICAL-c300t-b262dee1e0f8c3cef693660ba9b069191f3a00453d89a7b0f3e1ca8d99b90c833
ORCID 0000-0002-3345-5103
ParticipantIDs crossref_citationtrail_10_1016_j_bspc_2022_104198
crossref_primary_10_1016_j_bspc_2022_104198
elsevier_sciencedirect_doi_10_1016_j_bspc_2022_104198
PublicationCentury 2000
PublicationDate February 2023
2023-02-00
PublicationDateYYYYMMDD 2023-02-01
PublicationDate_xml – month: 02
  year: 2023
  text: February 2023
PublicationDecade 2020
PublicationTitle Biomedical signal processing and control
PublicationYear 2023
Publisher Elsevier Ltd
Publisher_xml – name: Elsevier Ltd
References Savur, Sahin (b58) 2016
Chicco, Jurman (b64) 2020; 21
Zia ur Rehman, Gilani, Waris, Niazi, Slabaugh, Farina, Kamavuako (b30) 2018; 8
Moritani, Muro, Nagata (b35) 1986; 60
Kumar, Mishra, Gautam, Bhushan (b2) 2021
Plamondon, Srihari (b3) 2000; 22
Dash, Sahu, Shringi, Gamboa, Afzal, Malik, Dengel, Ahmed (b11) 2017
Christ (b61) 2021
Neely, Rispoli, Camargo, Davis, Boles (b14) 2013; 7
Savur, Sahin (b45) 2015
Castellini, Van Der Smagt (b18) 2009; 100
Yu, Chen, Sheng, Zhu (b32) 2020; 57
Saeed, Zia-ur Rehman, Gilani, Amin, Waris, Jamil, Shafique (b44) 2021; 46
Beltran-Hernandez, Ruiz-Pinales, Lopez-Rodriguez, Lopez-Ramirez, Avina-Cervantes (b26) 2020; 17
Linderman, Lebedev, Erlichman (b5) 2009; 4
Bengio (b63) 2012
Jones, Oliphant, Peterson (b54) 2001
Li, Ma, Yao, Zhang (b25) 2013
Cascarano, Loconsole, Brunetti, Lattarulo, Buongiorno, Losavio, Di Sciascio, Bevilacqua (b80) 2019; 19
Too, Abdullah, Saad, Ali, Musa (b53) 2018; 8
Lu, Mao, Wang, Ding, Zhang (b7) 2020; 14
Okorokova, Lebedev, Linderman, Ossadtchi (b21) 2015; 9
Vujaklija, Shalchyan, Kamavuako, Jiang, Marateb, Farina (b31) 2018; 15
Kanoga, Kanemura, Asoh (b83) 2020; 60
Huang, Zhang, Zheng, Zhu (b24) 2010
Grandini, Bagli, Visani (b65) 2020
Y. Cao, A. Dhekne, M. Ammar, ITrackU: tracking a pen-like instrument via UWB-IMU fusion, in: Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services, 2021, pp. 453–466.
Asemi, Maghooli, Rahatabad, Azadeh (b82) 2022; 76
Chihi, Kamavuako, Benrejeb (b38) 2020
Chihi, Abdelkrim, Benrejeb (b19) 2017; 14
Reaz, Hussain, Mohd-Yasin (b39) 2006; 8
Drotár, Mekyska, Rektorová, Masarová, Smékal, Faundez-Zanuy (b16) 2014; 117
Schröter, Mergl, Bürger, Hampel, Möller, Hegerl (b17) 2003; 15
De Luca (b43) 2002; 10
Visconti, Gaetani, Zappatore, Primiceri (b41) 2018; 11
Dellacasa Bellingegni, Gruppioni, Colazzo, Davalli, Sacchetti, Guglielmelli, Zollo (b77) 2017; 14
Menon, Di Caterina, Lakany, Petropoulakis, Conway, Soraghan (b47) 2017; 25
Parajuli, Sreenivasan, Bifulco, Cesarelli, Savino, Niola, Esposito, Hamilton, Naik, Gunawardana (b49) 2019; 19
Tucha, Mecklinger, Thome, Reiter, Alders, Sartor, Naumann, Lange (b81) 2006; 113
Merletti, Farina (b37) 2009; 367
Jing, Dai, Zhou (b76) 2017
Wattenberg, Viégas, Johnson (b67) 2016
Bank, Koenigstein, Giryes (b28) 2020
Wu, Pan, Chen, Long, Zhang, Philip (b79) 2020; 32
Khan, Khan, Farooq (b46) 2019; 13
Friedrich, Siegert, Peinke, Siefert, Lindemann, Raethjen, Deuschl, Pfister (b57) 2000; 271
Ott, Wehbi, Hamann, Barth, Eskofier, Mutschler (b75) 2020; 4
Chihi, Abdelkrim, Benrejeb (b22) 2016; 110
Maharjan, Shrestha, Bhatta, Cho, Park, Salauddin, Rahman, Rana, Lee, Park (b9) 2021
Plamondon, Pirlo, Anquetil, Rémi, Teulings, Nakagawa (b13) 2018; 81
Wehbi, Hamann, Barth, Eskofier (b69) 2020
Adewuyi, Hargrove, Kuiken (b78) 2016; 10
Ahsan, Ibrahimy, Khalifa (b6) 2009; 33
Schreiber, Schmitz (b51) 1997; 55
Longstaff, Heath (b20) 1999; 18
Drotár, Mekyska, Rektorová, Masarová, Smékal, Faundez-Zanuy (b15) 2016; 67
Spüler, Irastorza-Landa, Sarasola-Sanz, Ramos-Murguialday (b29) 2016
F. Kerber, P. Schardt, M. Löchtefeld, WristRotate: a personalized motion gesture delimiter for wrist-worn devices, in: Proceedings of the 14th International Conference on Mobile and Ubiquitous Multimedia, 2015, pp. 218–222.
Smith, Hargrove (b36) 2013
Aboy, Hornero, Abásolo, Álvarez (b55) 2006; 53
Wang, Hsu, Chu (b72) 2013
Ng (b62) 2011
Plamondon, Lorette (b10) 1989; 22
Zhang, Bi, Chen, Wang, Han, Cai (b60) 2019; 7
Li, Zhang, Wang, Zhang, Li, Bao (b34) 2020; 62
Ison, Artemiadis (b48) 2014; 11
Nymoen, Haugen, Jensenius (b42) 2015
Di Domenico, Marinelli, Boccardo, Semprini, Lombardi, Canepa, Stedman, Bellingegni, Chiappalone, Gruppioni, Laffranchi, De Michieli (b73) 2021
Carter, Russell (b12) 1985; 18
Das, Singh, De, Chakraborty, Mitra (b1) 2020
Edwards, Dawson, Hebert, Sherstan, Sutton, Chan, Pilarski (b74) 2016; 40
Batista, Keogh, Tataw, De Souza (b52) 2014; 28
Song, Cao, Li, Wang, Liu (b40) 2021; 26
Yeh, Zhu, Ulanova, Begum, Ding, Dau, Silva, Mueen, Keogh (b56) 2016
Zhang, Chen, Li, Lantz, Wang, Yang (b50) 2011; 41
Van der Maaten, Hinton (b66) 2008; 9
Khan, Choudry, Aziz, Naqvi, Aymin, Imtiaz (b8) 2020
Hinton, Salakhutdinov (b27) 2006; 313
Chihi, Sidhom, Maamri (b23) 2018; 13
Li, Zhang, Sun, Kong (b33) 2019; 78
Priya, Mishra, Raj, Mandal, Datta (b4) 2016
M. Schrapel, M.-L. Stadler, M. Rohs, Pentelligence: Combining pen tip motion and writing sounds for handwritten digit recognition, in: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, 2018, pp. 1–11.
Wang, Chuang (b71) 2011; 59
Drotár (10.1016/j.bspc.2022.104198_b15) 2016; 67
Friedrich (10.1016/j.bspc.2022.104198_b57) 2000; 271
Cascarano (10.1016/j.bspc.2022.104198_b80) 2019; 19
Chihi (10.1016/j.bspc.2022.104198_b19) 2017; 14
Wang (10.1016/j.bspc.2022.104198_b71) 2011; 59
Spüler (10.1016/j.bspc.2022.104198_b29) 2016
Plamondon (10.1016/j.bspc.2022.104198_b3) 2000; 22
Huang (10.1016/j.bspc.2022.104198_b24) 2010
Zhang (10.1016/j.bspc.2022.104198_b60) 2019; 7
Drotár (10.1016/j.bspc.2022.104198_b16) 2014; 117
Chihi (10.1016/j.bspc.2022.104198_b22) 2016; 110
Khan (10.1016/j.bspc.2022.104198_b8) 2020
Plamondon (10.1016/j.bspc.2022.104198_b10) 1989; 22
Linderman (10.1016/j.bspc.2022.104198_b5) 2009; 4
Dash (10.1016/j.bspc.2022.104198_b11) 2017
Wu (10.1016/j.bspc.2022.104198_b79) 2020; 32
Kanoga (10.1016/j.bspc.2022.104198_b83) 2020; 60
Asemi (10.1016/j.bspc.2022.104198_b82) 2022; 76
10.1016/j.bspc.2022.104198_b68
Ison (10.1016/j.bspc.2022.104198_b48) 2014; 11
Savur (10.1016/j.bspc.2022.104198_b58) 2016
Nymoen (10.1016/j.bspc.2022.104198_b42) 2015
Vujaklija (10.1016/j.bspc.2022.104198_b31) 2018; 15
De Luca (10.1016/j.bspc.2022.104198_b43) 2002; 10
Zhang (10.1016/j.bspc.2022.104198_b50) 2011; 41
Merletti (10.1016/j.bspc.2022.104198_b37) 2009; 367
Jing (10.1016/j.bspc.2022.104198_b76) 2017
Parajuli (10.1016/j.bspc.2022.104198_b49) 2019; 19
Edwards (10.1016/j.bspc.2022.104198_b74) 2016; 40
Zia ur Rehman (10.1016/j.bspc.2022.104198_b30) 2018; 8
Longstaff (10.1016/j.bspc.2022.104198_b20) 1999; 18
Okorokova (10.1016/j.bspc.2022.104198_b21) 2015; 9
10.1016/j.bspc.2022.104198_b70
Moritani (10.1016/j.bspc.2022.104198_b35) 1986; 60
Li (10.1016/j.bspc.2022.104198_b33) 2019; 78
Maharjan (10.1016/j.bspc.2022.104198_b9) 2021
Schröter (10.1016/j.bspc.2022.104198_b17) 2003; 15
Wattenberg (10.1016/j.bspc.2022.104198_b67) 2016
Priya (10.1016/j.bspc.2022.104198_b4) 2016
Ahsan (10.1016/j.bspc.2022.104198_b6) 2009; 33
Di Domenico (10.1016/j.bspc.2022.104198_b73) 2021
Menon (10.1016/j.bspc.2022.104198_b47) 2017; 25
Too (10.1016/j.bspc.2022.104198_b53) 2018; 8
Beltran-Hernandez (10.1016/j.bspc.2022.104198_b26) 2020; 17
10.1016/j.bspc.2022.104198_b59
Plamondon (10.1016/j.bspc.2022.104198_b13) 2018; 81
Reaz (10.1016/j.bspc.2022.104198_b39) 2006; 8
Khan (10.1016/j.bspc.2022.104198_b46) 2019; 13
Grandini (10.1016/j.bspc.2022.104198_b65) 2020
Chicco (10.1016/j.bspc.2022.104198_b64) 2020; 21
Tucha (10.1016/j.bspc.2022.104198_b81) 2006; 113
Hinton (10.1016/j.bspc.2022.104198_b27) 2006; 313
Song (10.1016/j.bspc.2022.104198_b40) 2021; 26
Saeed (10.1016/j.bspc.2022.104198_b44) 2021; 46
Bank (10.1016/j.bspc.2022.104198_b28) 2020
Kumar (10.1016/j.bspc.2022.104198_b2) 2021
Li (10.1016/j.bspc.2022.104198_b34) 2020; 62
Adewuyi (10.1016/j.bspc.2022.104198_b78) 2016; 10
Smith (10.1016/j.bspc.2022.104198_b36) 2013
Schreiber (10.1016/j.bspc.2022.104198_b51) 1997; 55
Batista (10.1016/j.bspc.2022.104198_b52) 2014; 28
Aboy (10.1016/j.bspc.2022.104198_b55) 2006; 53
Carter (10.1016/j.bspc.2022.104198_b12) 1985; 18
Wang (10.1016/j.bspc.2022.104198_b72) 2013
Yeh (10.1016/j.bspc.2022.104198_b56) 2016
Van der Maaten (10.1016/j.bspc.2022.104198_b66) 2008; 9
Christ (10.1016/j.bspc.2022.104198_b61) 2021
Jones (10.1016/j.bspc.2022.104198_b54) 2001
Wehbi (10.1016/j.bspc.2022.104198_b69) 2020
Lu (10.1016/j.bspc.2022.104198_b7) 2020; 14
Chihi (10.1016/j.bspc.2022.104198_b38) 2020
Dellacasa Bellingegni (10.1016/j.bspc.2022.104198_b77) 2017; 14
Yu (10.1016/j.bspc.2022.104198_b32) 2020; 57
Visconti (10.1016/j.bspc.2022.104198_b41) 2018; 11
Savur (10.1016/j.bspc.2022.104198_b45) 2015
Bengio (10.1016/j.bspc.2022.104198_b63) 2012
Das (10.1016/j.bspc.2022.104198_b1) 2020
Neely (10.1016/j.bspc.2022.104198_b14) 2013; 7
Chihi (10.1016/j.bspc.2022.104198_b23) 2018; 13
Castellini (10.1016/j.bspc.2022.104198_b18) 2009; 100
Ng (10.1016/j.bspc.2022.104198_b62) 2011
Li (10.1016/j.bspc.2022.104198_b25) 2013
Ott (10.1016/j.bspc.2022.104198_b75) 2020; 4
References_xml – start-page: 2144
  year: 2013
  end-page: 2147
  ident: b25
  article-title: Improvements on EMG-based handwriting recognition with DTW algorithm
  publication-title: 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
– start-page: 5997
  year: 2021
  end-page: 6002
  ident: b73
  article-title: Hannes prosthesis control based on regression machine learning algorithms
  publication-title: 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
– volume: 33
  start-page: 480
  year: 2009
  end-page: 501
  ident: b6
  article-title: EMG signal classification for human computer interaction: a review
  publication-title: Eur. J. Sci. Res.
– start-page: 1
  year: 2020
  end-page: 5
  ident: b8
  article-title: Biometric authentication based on EMG signals of speech
  publication-title: 2020 International Conference on Electrical, Communication, and Computer Engineering (ICECCE)
– year: 2020
  ident: b65
  article-title: Metrics for multi-class classification: an overview
– volume: 26
  start-page: 692
  year: 2021
  end-page: 705
  ident: b40
  article-title: Inertial motion tracking on mobile and wearable devices: Recent advancements and challenges
  publication-title: Tsinghua Sci. Technol.
– volume: 46
  start-page: 1761
  year: 2021
  end-page: 1769
  ident: b44
  article-title: Leveraging ANN and LDA classifiers for characterizing different hand movements using emg signals
  publication-title: Arab. J. Sci. Eng.
– volume: 25
  start-page: 1832
  year: 2017
  end-page: 1842
  ident: b47
  article-title: Study on interaction between temporal and spatial information in classification of EMG signals for myoelectric prostheses
  publication-title: IEEE Trans. Neural Syst. Rehabil. Eng.
– volume: 53
  start-page: 2282
  year: 2006
  end-page: 2288
  ident: b55
  article-title: Interpretation of the Lempel-Ziv complexity measure in the context of biomedical signal analysis
  publication-title: IEEE Trans. Biomed. Eng.
– volume: 76
  year: 2022
  ident: b82
  article-title: Handwritten signatures verification based on arm and hand muscles synergy
  publication-title: Biomed. Signal Process. Control
– volume: 9
  start-page: 389
  year: 2015
  ident: b21
  article-title: A dynamical model improves reconstruction of handwriting from multichannel electromyographic recordings
  publication-title: Front. Neurosci.
– year: 2001
  ident: b54
  article-title: SciPy: Open source scientific tools for Python
– volume: 22
  start-page: 107
  year: 1989
  end-page: 131
  ident: b10
  article-title: Automatic signature verification and writer identification—the state of the art
  publication-title: Pattern Recognit.
– year: 2015
  ident: b42
  article-title: Mumyo–evaluating and exploring the myo armband for musical interaction
– volume: 41
  start-page: 1064
  year: 2011
  end-page: 1076
  ident: b50
  article-title: A framework for hand gesture recognition based on accelerometer and EMG sensors
  publication-title: IEEE Trans. Syst., Man, Cybern.-Part A: Syst. Hum.
– start-page: 0967
  year: 2016
  end-page: 0970
  ident: b4
  article-title: Online and offline character recognition: A survey
  publication-title: 2016 International Conference on Communication and Signal Processing (ICCSP)
– start-page: 4223
  year: 2013
  end-page: 4226
  ident: b36
  article-title: Comparison of surface and intramuscular EMG pattern recognition for simultaneous wrist/hand motion classification
  publication-title: 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
– start-page: 908
  year: 2017
  end-page: 913
  ident: b11
  article-title: Airscript-creating documents in air
  publication-title: 2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR), Vol. 1
– volume: 110
  start-page: 17
  year: 2016
  end-page: 30
  ident: b22
  article-title: Multi-model approach to characterize human handwriting motion
  publication-title: Biol. Cybernet.
– volume: 8
  start-page: 1126
  year: 2018
  ident: b30
  article-title: Stacked sparse autoencoders for EMG-based classification of hand motions: A comparative multi day analyses between surface and intramuscular EMG
  publication-title: Appl. Sci.
– volume: 313
  start-page: 504
  year: 2006
  end-page: 507
  ident: b27
  article-title: Reducing the dimensionality of data with neural networks
  publication-title: Science
– year: 2021
  ident: b9
  article-title: Keystroke dynamics based hybrid nanogenerators for biometric authentication and identification using artificial intelligence
  publication-title: Adv. Sci.
– volume: 367
  start-page: 357
  year: 2009
  end-page: 368
  ident: b37
  article-title: Analysis of intramuscular electromyogram signals
  publication-title: Phil. Trans. R. Soc. A
– start-page: 1
  year: 2020
  end-page: 5
  ident: b1
  article-title: Note-on-watch: Live scribing from board-works to class-notes
  publication-title: 22nd International Conference on Human-Computer Interaction with Mobile Devices and Services
– volume: 18
  start-page: 213
  year: 1985
  end-page: 216
  ident: b12
  article-title: Use of EMG biofeedback procedures with learning disabled children in a clinical and an educational setting
  publication-title: J. Learn. Disabil.
– volume: 14
  start-page: 861
  year: 2017
  end-page: 869
  ident: b19
  article-title: Internal model control to characterize human handwriting motion
  publication-title: Int. Arab J. Inf. Technol.
– volume: 55
  start-page: 5443
  year: 1997
  ident: b51
  article-title: Discrimination power of measures for nonlinearity in a time series
  publication-title: Phys. Rev. E
– volume: 15
  start-page: 1
  year: 2018
  end-page: 9
  ident: b31
  article-title: Online mapping of EMG signals into kinematics by autoencoding
  publication-title: J. Neuroeng. Rehabil.
– volume: 59
  start-page: 2998
  year: 2011
  end-page: 3007
  ident: b71
  article-title: An accelerometer-based digital pen with a trajectory recognition algorithm for handwritten digit and gesture recognition
  publication-title: IEEE Trans. Ind. Electron.
– volume: 7
  start-page: 960
  year: 2019
  end-page: 970
  ident: b60
  article-title: SmartHandwriting: Handwritten Chinese character recognition with smartwatch
  publication-title: IEEE Internet Things J.
– volume: 4
  year: 2009
  ident: b5
  article-title: Recognition of handwriting from electromyography
  publication-title: PLoS One
– volume: 19
  start-page: 4596
  year: 2019
  ident: b49
  article-title: Real-time EMG based pattern recognition control for hand prostheses: a review on existing methods, challenges and future implementation
  publication-title: Sensors
– start-page: 621
  year: 2021
  end-page: 632
  ident: b2
  article-title: Handwritten signature verification system using IoT
  publication-title: Emerging Technologies in Data Mining and Information Security
– volume: 100
  start-page: 35
  year: 2009
  end-page: 47
  ident: b18
  article-title: Surface EMG in advanced hand prosthetics
  publication-title: Biol. Cybernet.
– start-page: 1330
  year: 2017
  end-page: 1337
  ident: b76
  article-title: Wearable handwriting recognition with an inertial sensor on a finger nail
  publication-title: 2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR), Vol. 1
– volume: 17
  start-page: 5432
  year: 2020
  end-page: 5448
  ident: b26
  article-title: Multi-stroke handwriting character recognition based on sEMG using convolutional-recurrent neural networks
  publication-title: Math. Biosci. Eng.
– volume: 22
  start-page: 63
  year: 2000
  end-page: 84
  ident: b3
  article-title: Online and off-line handwriting recognition: a comprehensive survey
  publication-title: IEEE Trans. Pattern Anal. Mach. Intell.
– volume: 62
  year: 2020
  ident: b34
  article-title: A review of the key technologies for sEMG-based human-robot interaction systems
  publication-title: Biomed. Signal Process. Control
– volume: 10
  start-page: 1
  year: 2002
  end-page: 10
  ident: b43
  article-title: Surface electromyography: Detection and recording
  publication-title: DelSys Incorporated
– year: 2016
  ident: b67
  article-title: How to use t-SNE effectively
– volume: 11
  year: 2014
  ident: b48
  article-title: The role of muscle synergies in myoelectric control: trends and challenges for simultaneous multifunction control
  publication-title: J. Neural Eng.
– reference: Y. Cao, A. Dhekne, M. Ammar, ITrackU: tracking a pen-like instrument via UWB-IMU fusion, in: Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services, 2021, pp. 453–466.
– year: 2020
  ident: b28
  article-title: Autoencoders
– volume: 21
  start-page: 1
  year: 2020
  end-page: 13
  ident: b64
  article-title: The advantages of the matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation
  publication-title: BMC Genomics
– year: 2021
  ident: b61
  article-title: Tsfresh
– volume: 14
  start-page: 681
  year: 2020
  end-page: 691
  ident: b7
  article-title: A study of personal recognition method based on EMG signal
  publication-title: IEEE Trans. Biomed. Circuits Syst.
– reference: F. Kerber, P. Schardt, M. Löchtefeld, WristRotate: a personalized motion gesture delimiter for wrist-worn devices, in: Proceedings of the 14th International Conference on Mobile and Ubiquitous Multimedia, 2015, pp. 218–222.
– volume: 67
  start-page: 39
  year: 2016
  end-page: 46
  ident: b15
  article-title: Evaluation of handwriting kinematics and pressure for differential diagnosis of Parkinson’s disease
  publication-title: Artif. Intell. Med.
– start-page: 1
  year: 2011
  end-page: 19
  ident: b62
  publication-title: Sparse Autoencoder, Vol. 72
– volume: 8
  start-page: 4221
  year: 2018
  end-page: 4229
  ident: b53
  article-title: A detail study of wavelet families for EMG pattern recognition
  publication-title: Int. J. Electr. Comput. Eng. (IJECE)
– reference: M. Schrapel, M.-L. Stadler, M. Rohs, Pentelligence: Combining pen tip motion and writing sounds for handwritten digit recognition, in: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, 2018, pp. 1–11.
– volume: 19
  start-page: 1
  year: 2019
  end-page: 11
  ident: b80
  article-title: Biometric handwriting analysis to support Parkinson’s Disease assessment and grading
  publication-title: BMC Med. Inf. Decis. Making
– volume: 15
  start-page: 132
  year: 2003
  end-page: 142
  ident: b17
  article-title: Kinematic analysis of handwriting movements in patients with Alzheimer’s disease, mild cognitive impairment, depression and healthy subjects
  publication-title: Dementia Geriatr. Cogn. Disord.
– start-page: 002872
  year: 2016
  end-page: 002877
  ident: b58
  article-title: American sign language recognition system by using surface EMG signal
  publication-title: 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC)
– volume: 60
  start-page: 1179
  year: 1986
  end-page: 1185
  ident: b35
  article-title: Intramuscular and surface electromyogram changes during muscle fatigue
  publication-title: J. Appl. Physiol.
– start-page: 229
  year: 2013
  end-page: 232
  ident: b72
  article-title: Online handwriting recognition using an accelerometer-based pen device
  publication-title: 2nd International Conference on Advances in Computer Science and Engineering
– volume: 57
  year: 2020
  ident: b32
  article-title: Multi-DoF continuous estimation for wrist torques using stacked autoencoder
  publication-title: Biomed. Signal Process. Control
– start-page: 1317
  year: 2016
  end-page: 1322
  ident: b56
  article-title: Matrix profile I: all pairs similarity joins for time series: a unifying view that includes motifs, discords and shapelets
  publication-title: 2016 IEEE 16th International Conference on Data Mining (ICDM)
– volume: 32
  start-page: 4
  year: 2020
  end-page: 24
  ident: b79
  article-title: A comprehensive survey on graph neural networks
  publication-title: IEEE Trans. Neural Netw. Learn. Syst.
– volume: 18
  start-page: 485
  year: 1999
  end-page: 524
  ident: b20
  article-title: A nonlinear analysis of the temporal characteristics of handwriting
  publication-title: Hum. Mov. Sci.
– volume: 40
  start-page: 573
  year: 2016
  end-page: 581
  ident: b74
  article-title: Application of real-time machine learning to myoelectric prosthesis control: A case series in adaptive switching
  publication-title: Prosthet. Orthot. Int.
– start-page: 129
  year: 2020
  end-page: 149
  ident: b38
  article-title: Modeling simple and complex handwriting based on EMG signals
  publication-title: Control Theory Biomed. Eng.
– volume: 78
  start-page: 29765
  year: 2019
  end-page: 29782
  ident: b33
  article-title: Towards the sEMG hand: internet of things sensors and haptic feedback application
  publication-title: Multimedia Tools Appl.
– volume: 81
  start-page: 633
  year: 2018
  end-page: 659
  ident: b13
  article-title: Personal digital bodyguards for e-security, e-learning and e-health: A prospective survey
  publication-title: Pattern Recognit.
– start-page: 295
  year: 2020
  end-page: 300
  ident: b69
  article-title: Digitizing handwriting with a sensor pen: A writer-independent recognizer
  publication-title: 2020 17th International Conference on Frontiers in Handwriting Recognition (ICFHR)
– volume: 8
  start-page: 163
  year: 2006
  ident: b39
  article-title: Techniques of EMG signal analysis: detection, processing, classification and applications (Correction)
  publication-title: Biol. Proced. Online
– volume: 113
  start-page: 609
  year: 2006
  end-page: 623
  ident: b81
  article-title: Kinematic analysis of dopaminergic effects on skilled handwriting movements in Parkinson’s disease
  publication-title: J. Neural Transm.
– volume: 117
  start-page: 405
  year: 2014
  end-page: 411
  ident: b16
  article-title: Analysis of in-air movement in handwriting: A novel marker for Parkinson’s disease
  publication-title: Comput. Methods Programs Biomed.
– start-page: 497
  year: 2015
  end-page: 502
  ident: b45
  article-title: Real-time american sign language recognition system using surface emg signal
  publication-title: 2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA)
– start-page: 4902
  year: 2010
  end-page: 4905
  ident: b24
  article-title: An EMG-based handwriting recognition through dynamic time warping
  publication-title: 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology
– volume: 13
  start-page: 248
  year: 2019
  end-page: 260
  ident: b46
  article-title: Selection of features and classifiers for EMG-EEG-Based upper limb assistive devices—a review
  publication-title: IEEE Rev. Biomed. Eng.
– volume: 9
  year: 2008
  ident: b66
  article-title: Visualizing data using t-SNE
  publication-title: J. Mach. Learn. Res.
– volume: 4
  start-page: 1
  year: 2020
  end-page: 20
  ident: b75
  article-title: The OnHW dataset: Online handwriting recognition from IMU-enhanced ballpoint pens with machine learning
  publication-title: Proc. ACM Interact., Mob., Wearable Ubiquitous Technol.
– volume: 271
  start-page: 217
  year: 2000
  end-page: 222
  ident: b57
  article-title: Extracting model equations from experimental data
  publication-title: Phys. Lett. A
– start-page: 47
  year: 2016
  end-page: 54
  ident: b29
  article-title: Extracting muscle synergy patterns from EMG data using autoencoders
  publication-title: International Conference on Artificial Neural Networks
– volume: 11
  start-page: 1
  year: 2018
  end-page: 25
  ident: b41
  article-title: Technical features and functionalities of Myo armband: An overview on related literature and advanced applications of myoelectric armbands mainly focused on arm prostheses
  publication-title: Int. J. Smart Sens. Intell. Syst.
– volume: 14
  start-page: 1
  year: 2017
  end-page: 16
  ident: b77
  article-title: NLR, MLP, SVM, and LDA: a comparative analysis on EMG data from people with trans-radial amputation
  publication-title: J. Neuroeng. Rehabil.
– volume: 7
  start-page: 509
  year: 2013
  end-page: 516
  ident: b14
  article-title: The effect of instructional use of an iPad® on challenging behavior and academic engagement for two students with autism
  publication-title: Res. Autism Spectr. Disord.
– volume: 28
  start-page: 634
  year: 2014
  end-page: 669
  ident: b52
  article-title: CID: an efficient complexity-invariant distance for time series
  publication-title: Data Min. Knowl. Discov.
– volume: 60
  year: 2020
  ident: b83
  article-title: Are armband sEMG devices dense enough for long-term use?—Sensor placement shifts cause significant reduction in recognition accuracy
  publication-title: Biomed. Signal Process. Control
– volume: 13
  start-page: 16213
  year: 2018
  end-page: 16219
  ident: b23
  article-title: Robust handwriting estimator from two forearm muscles activities
  publication-title: Int. J. Appl. Eng. Res.
– start-page: 437
  year: 2012
  end-page: 478
  ident: b63
  article-title: Practical recommendations for gradient-based training of deep architectures
  publication-title: Neural Networks: Tricks of the Trade
– volume: 10
  start-page: 15
  year: 2016
  ident: b78
  article-title: Evaluating EMG feature and classifier selection for application to partial-hand prosthesis control
  publication-title: Front. Neurorobotics
– volume: 78
  start-page: 29765
  issue: 21
  year: 2019
  ident: 10.1016/j.bspc.2022.104198_b33
  article-title: Towards the sEMG hand: internet of things sensors and haptic feedback application
  publication-title: Multimedia Tools Appl.
  doi: 10.1007/s11042-018-6293-x
– start-page: 2144
  year: 2013
  ident: 10.1016/j.bspc.2022.104198_b25
  article-title: Improvements on EMG-based handwriting recognition with DTW algorithm
– year: 2021
  ident: 10.1016/j.bspc.2022.104198_b9
  article-title: Keystroke dynamics based hybrid nanogenerators for biometric authentication and identification using artificial intelligence
  publication-title: Adv. Sci.
  doi: 10.1002/advs.202100711
– start-page: 5997
  year: 2021
  ident: 10.1016/j.bspc.2022.104198_b73
  article-title: Hannes prosthesis control based on regression machine learning algorithms
– volume: 32
  start-page: 4
  issue: 1
  year: 2020
  ident: 10.1016/j.bspc.2022.104198_b79
  article-title: A comprehensive survey on graph neural networks
  publication-title: IEEE Trans. Neural Netw. Learn. Syst.
  doi: 10.1109/TNNLS.2020.2978386
– start-page: 1
  year: 2020
  ident: 10.1016/j.bspc.2022.104198_b8
  article-title: Biometric authentication based on EMG signals of speech
– volume: 19
  start-page: 1
  issue: 9
  year: 2019
  ident: 10.1016/j.bspc.2022.104198_b80
  article-title: Biometric handwriting analysis to support Parkinson’s Disease assessment and grading
  publication-title: BMC Med. Inf. Decis. Making
– volume: 21
  start-page: 1
  issue: 1
  year: 2020
  ident: 10.1016/j.bspc.2022.104198_b64
  article-title: The advantages of the matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation
  publication-title: BMC Genomics
  doi: 10.1186/s12864-019-6413-7
– volume: 117
  start-page: 405
  issue: 3
  year: 2014
  ident: 10.1016/j.bspc.2022.104198_b16
  article-title: Analysis of in-air movement in handwriting: A novel marker for Parkinson’s disease
  publication-title: Comput. Methods Programs Biomed.
  doi: 10.1016/j.cmpb.2014.08.007
– volume: 46
  start-page: 1761
  issue: 2
  year: 2021
  ident: 10.1016/j.bspc.2022.104198_b44
  article-title: Leveraging ANN and LDA classifiers for characterizing different hand movements using emg signals
  publication-title: Arab. J. Sci. Eng.
  doi: 10.1007/s13369-020-05044-x
– volume: 22
  start-page: 63
  issue: 1
  year: 2000
  ident: 10.1016/j.bspc.2022.104198_b3
  article-title: Online and off-line handwriting recognition: a comprehensive survey
  publication-title: IEEE Trans. Pattern Anal. Mach. Intell.
  doi: 10.1109/34.824821
– volume: 13
  start-page: 248
  year: 2019
  ident: 10.1016/j.bspc.2022.104198_b46
  article-title: Selection of features and classifiers for EMG-EEG-Based upper limb assistive devices—a review
  publication-title: IEEE Rev. Biomed. Eng.
  doi: 10.1109/RBME.2019.2950897
– volume: 110
  start-page: 17
  issue: 1
  year: 2016
  ident: 10.1016/j.bspc.2022.104198_b22
  article-title: Multi-model approach to characterize human handwriting motion
  publication-title: Biol. Cybernet.
  doi: 10.1007/s00422-015-0670-6
– volume: 25
  start-page: 1832
  issue: 10
  year: 2017
  ident: 10.1016/j.bspc.2022.104198_b47
  article-title: Study on interaction between temporal and spatial information in classification of EMG signals for myoelectric prostheses
  publication-title: IEEE Trans. Neural Syst. Rehabil. Eng.
  doi: 10.1109/TNSRE.2017.2687761
– volume: 4
  start-page: 1
  issue: 3
  year: 2020
  ident: 10.1016/j.bspc.2022.104198_b75
  article-title: The OnHW dataset: Online handwriting recognition from IMU-enhanced ballpoint pens with machine learning
  publication-title: Proc. ACM Interact., Mob., Wearable Ubiquitous Technol.
  doi: 10.1145/3411842
– volume: 14
  start-page: 1
  issue: 1
  year: 2017
  ident: 10.1016/j.bspc.2022.104198_b77
  article-title: NLR, MLP, SVM, and LDA: a comparative analysis on EMG data from people with trans-radial amputation
  publication-title: J. Neuroeng. Rehabil.
– ident: 10.1016/j.bspc.2022.104198_b68
  doi: 10.1145/3458864.3467885
– volume: 57
  year: 2020
  ident: 10.1016/j.bspc.2022.104198_b32
  article-title: Multi-DoF continuous estimation for wrist torques using stacked autoencoder
  publication-title: Biomed. Signal Process. Control
  doi: 10.1016/j.bspc.2019.101733
– volume: 60
  year: 2020
  ident: 10.1016/j.bspc.2022.104198_b83
  article-title: Are armband sEMG devices dense enough for long-term use?—Sensor placement shifts cause significant reduction in recognition accuracy
  publication-title: Biomed. Signal Process. Control
  doi: 10.1016/j.bspc.2020.101981
– volume: 18
  start-page: 485
  issue: 4
  year: 1999
  ident: 10.1016/j.bspc.2022.104198_b20
  article-title: A nonlinear analysis of the temporal characteristics of handwriting
  publication-title: Hum. Mov. Sci.
  doi: 10.1016/S0167-9457(99)00028-7
– volume: 76
  year: 2022
  ident: 10.1016/j.bspc.2022.104198_b82
  article-title: Handwritten signatures verification based on arm and hand muscles synergy
  publication-title: Biomed. Signal Process. Control
  doi: 10.1016/j.bspc.2022.103697
– volume: 81
  start-page: 633
  year: 2018
  ident: 10.1016/j.bspc.2022.104198_b13
  article-title: Personal digital bodyguards for e-security, e-learning and e-health: A prospective survey
  publication-title: Pattern Recognit.
  doi: 10.1016/j.patcog.2018.04.012
– start-page: 4223
  year: 2013
  ident: 10.1016/j.bspc.2022.104198_b36
  article-title: Comparison of surface and intramuscular EMG pattern recognition for simultaneous wrist/hand motion classification
– start-page: 002872
  year: 2016
  ident: 10.1016/j.bspc.2022.104198_b58
  article-title: American sign language recognition system by using surface EMG signal
– volume: 14
  start-page: 681
  issue: 4
  year: 2020
  ident: 10.1016/j.bspc.2022.104198_b7
  article-title: A study of personal recognition method based on EMG signal
  publication-title: IEEE Trans. Biomed. Circuits Syst.
  doi: 10.1109/TBCAS.2020.3005148
– start-page: 0967
  year: 2016
  ident: 10.1016/j.bspc.2022.104198_b4
  article-title: Online and offline character recognition: A survey
– volume: 62
  year: 2020
  ident: 10.1016/j.bspc.2022.104198_b34
  article-title: A review of the key technologies for sEMG-based human-robot interaction systems
  publication-title: Biomed. Signal Process. Control
  doi: 10.1016/j.bspc.2020.102074
– volume: 10
  start-page: 15
  year: 2016
  ident: 10.1016/j.bspc.2022.104198_b78
  article-title: Evaluating EMG feature and classifier selection for application to partial-hand prosthesis control
  publication-title: Front. Neurorobotics
  doi: 10.3389/fnbot.2016.00015
– start-page: 295
  year: 2020
  ident: 10.1016/j.bspc.2022.104198_b69
  article-title: Digitizing handwriting with a sensor pen: A writer-independent recognizer
– volume: 22
  start-page: 107
  issue: 2
  year: 1989
  ident: 10.1016/j.bspc.2022.104198_b10
  article-title: Automatic signature verification and writer identification—the state of the art
  publication-title: Pattern Recognit.
  doi: 10.1016/0031-3203(89)90059-9
– volume: 55
  start-page: 5443
  issue: 5
  year: 1997
  ident: 10.1016/j.bspc.2022.104198_b51
  article-title: Discrimination power of measures for nonlinearity in a time series
  publication-title: Phys. Rev. E
  doi: 10.1103/PhysRevE.55.5443
– year: 2016
  ident: 10.1016/j.bspc.2022.104198_b67
– volume: 28
  start-page: 634
  issue: 3
  year: 2014
  ident: 10.1016/j.bspc.2022.104198_b52
  article-title: CID: an efficient complexity-invariant distance for time series
  publication-title: Data Min. Knowl. Discov.
  doi: 10.1007/s10618-013-0312-3
– ident: 10.1016/j.bspc.2022.104198_b59
  doi: 10.1145/2836041.2836063
– start-page: 908
  year: 2017
  ident: 10.1016/j.bspc.2022.104198_b11
  article-title: Airscript-creating documents in air
– start-page: 1317
  year: 2016
  ident: 10.1016/j.bspc.2022.104198_b56
  article-title: Matrix profile I: all pairs similarity joins for time series: a unifying view that includes motifs, discords and shapelets
– volume: 9
  start-page: 389
  year: 2015
  ident: 10.1016/j.bspc.2022.104198_b21
  article-title: A dynamical model improves reconstruction of handwriting from multichannel electromyographic recordings
  publication-title: Front. Neurosci.
  doi: 10.3389/fnins.2015.00389
– start-page: 229
  year: 2013
  ident: 10.1016/j.bspc.2022.104198_b72
  article-title: Online handwriting recognition using an accelerometer-based pen device
– volume: 15
  start-page: 132
  issue: 3
  year: 2003
  ident: 10.1016/j.bspc.2022.104198_b17
  article-title: Kinematic analysis of handwriting movements in patients with Alzheimer’s disease, mild cognitive impairment, depression and healthy subjects
  publication-title: Dementia Geriatr. Cogn. Disord.
  doi: 10.1159/000068484
– volume: 13
  start-page: 16213
  issue: 23
  year: 2018
  ident: 10.1016/j.bspc.2022.104198_b23
  article-title: Robust handwriting estimator from two forearm muscles activities
  publication-title: Int. J. Appl. Eng. Res.
– volume: 33
  start-page: 480
  issue: 3
  year: 2009
  ident: 10.1016/j.bspc.2022.104198_b6
  article-title: EMG signal classification for human computer interaction: a review
  publication-title: Eur. J. Sci. Res.
– year: 2020
  ident: 10.1016/j.bspc.2022.104198_b65
– volume: 18
  start-page: 213
  issue: 4
  year: 1985
  ident: 10.1016/j.bspc.2022.104198_b12
  article-title: Use of EMG biofeedback procedures with learning disabled children in a clinical and an educational setting
  publication-title: J. Learn. Disabil.
  doi: 10.1177/002221948501800406
– volume: 59
  start-page: 2998
  issue: 7
  year: 2011
  ident: 10.1016/j.bspc.2022.104198_b71
  article-title: An accelerometer-based digital pen with a trajectory recognition algorithm for handwritten digit and gesture recognition
  publication-title: IEEE Trans. Ind. Electron.
  doi: 10.1109/TIE.2011.2167895
– volume: 11
  issue: 5
  year: 2014
  ident: 10.1016/j.bspc.2022.104198_b48
  article-title: The role of muscle synergies in myoelectric control: trends and challenges for simultaneous multifunction control
  publication-title: J. Neural Eng.
  doi: 10.1088/1741-2560/11/5/051001
– volume: 313
  start-page: 504
  issue: 5786
  year: 2006
  ident: 10.1016/j.bspc.2022.104198_b27
  article-title: Reducing the dimensionality of data with neural networks
  publication-title: Science
  doi: 10.1126/science.1127647
– volume: 113
  start-page: 609
  issue: 5
  year: 2006
  ident: 10.1016/j.bspc.2022.104198_b81
  article-title: Kinematic analysis of dopaminergic effects on skilled handwriting movements in Parkinson’s disease
  publication-title: J. Neural Transm.
  doi: 10.1007/s00702-005-0346-9
– start-page: 621
  year: 2021
  ident: 10.1016/j.bspc.2022.104198_b2
  article-title: Handwritten signature verification system using IoT
– start-page: 1
  year: 2020
  ident: 10.1016/j.bspc.2022.104198_b1
  article-title: Note-on-watch: Live scribing from board-works to class-notes
– volume: 14
  start-page: 861
  issue: 6
  year: 2017
  ident: 10.1016/j.bspc.2022.104198_b19
  article-title: Internal model control to characterize human handwriting motion
  publication-title: Int. Arab J. Inf. Technol.
– volume: 9
  issue: 11
  year: 2008
  ident: 10.1016/j.bspc.2022.104198_b66
  article-title: Visualizing data using t-SNE
  publication-title: J. Mach. Learn. Res.
– volume: 19
  start-page: 4596
  issue: 20
  year: 2019
  ident: 10.1016/j.bspc.2022.104198_b49
  article-title: Real-time EMG based pattern recognition control for hand prostheses: a review on existing methods, challenges and future implementation
  publication-title: Sensors
  doi: 10.3390/s19204596
– volume: 53
  start-page: 2282
  issue: 11
  year: 2006
  ident: 10.1016/j.bspc.2022.104198_b55
  article-title: Interpretation of the Lempel-Ziv complexity measure in the context of biomedical signal analysis
  publication-title: IEEE Trans. Biomed. Eng.
  doi: 10.1109/TBME.2006.883696
– ident: 10.1016/j.bspc.2022.104198_b70
  doi: 10.1145/3173574.3173705
– volume: 40
  start-page: 573
  issue: 5
  year: 2016
  ident: 10.1016/j.bspc.2022.104198_b74
  article-title: Application of real-time machine learning to myoelectric prosthesis control: A case series in adaptive switching
  publication-title: Prosthet. Orthot. Int.
  doi: 10.1177/0309364615605373
– volume: 367
  start-page: 357
  issue: 1887
  year: 2009
  ident: 10.1016/j.bspc.2022.104198_b37
  article-title: Analysis of intramuscular electromyogram signals
  publication-title: Phil. Trans. R. Soc. A
  doi: 10.1098/rsta.2008.0235
– start-page: 1
  year: 2011
  ident: 10.1016/j.bspc.2022.104198_b62
– start-page: 497
  year: 2015
  ident: 10.1016/j.bspc.2022.104198_b45
  article-title: Real-time american sign language recognition system using surface emg signal
– volume: 7
  start-page: 509
  issue: 4
  year: 2013
  ident: 10.1016/j.bspc.2022.104198_b14
  article-title: The effect of instructional use of an iPad® on challenging behavior and academic engagement for two students with autism
  publication-title: Res. Autism Spectr. Disord.
  doi: 10.1016/j.rasd.2012.12.004
– start-page: 4902
  year: 2010
  ident: 10.1016/j.bspc.2022.104198_b24
  article-title: An EMG-based handwriting recognition through dynamic time warping
– volume: 8
  start-page: 163
  issue: 1
  year: 2006
  ident: 10.1016/j.bspc.2022.104198_b39
  article-title: Techniques of EMG signal analysis: detection, processing, classification and applications (Correction)
  publication-title: Biol. Proced. Online
  doi: 10.1251/bpo124
– year: 2001
  ident: 10.1016/j.bspc.2022.104198_b54
– volume: 100
  start-page: 35
  issue: 1
  year: 2009
  ident: 10.1016/j.bspc.2022.104198_b18
  article-title: Surface EMG in advanced hand prosthetics
  publication-title: Biol. Cybernet.
  doi: 10.1007/s00422-008-0278-1
– volume: 11
  start-page: 1
  issue: 1
  year: 2018
  ident: 10.1016/j.bspc.2022.104198_b41
  article-title: Technical features and functionalities of Myo armband: An overview on related literature and advanced applications of myoelectric armbands mainly focused on arm prostheses
  publication-title: Int. J. Smart Sens. Intell. Syst.
– year: 2020
  ident: 10.1016/j.bspc.2022.104198_b28
– volume: 271
  start-page: 217
  issue: 3
  year: 2000
  ident: 10.1016/j.bspc.2022.104198_b57
  article-title: Extracting model equations from experimental data
  publication-title: Phys. Lett. A
  doi: 10.1016/S0375-9601(00)00334-0
– start-page: 1330
  year: 2017
  ident: 10.1016/j.bspc.2022.104198_b76
  article-title: Wearable handwriting recognition with an inertial sensor on a finger nail
– volume: 7
  start-page: 960
  issue: 2
  year: 2019
  ident: 10.1016/j.bspc.2022.104198_b60
  article-title: SmartHandwriting: Handwritten Chinese character recognition with smartwatch
  publication-title: IEEE Internet Things J.
  doi: 10.1109/JIOT.2019.2947448
– start-page: 129
  year: 2020
  ident: 10.1016/j.bspc.2022.104198_b38
  article-title: Modeling simple and complex handwriting based on EMG signals
  publication-title: Control Theory Biomed. Eng.
  doi: 10.1016/B978-0-12-821350-6.00006-8
– volume: 8
  start-page: 4221
  issue: 6
  year: 2018
  ident: 10.1016/j.bspc.2022.104198_b53
  article-title: A detail study of wavelet families for EMG pattern recognition
  publication-title: Int. J. Electr. Comput. Eng. (IJECE)
  doi: 10.11591/ijece.v8i6.pp4221-4229
– volume: 41
  start-page: 1064
  issue: 6
  year: 2011
  ident: 10.1016/j.bspc.2022.104198_b50
  article-title: A framework for hand gesture recognition based on accelerometer and EMG sensors
  publication-title: IEEE Trans. Syst., Man, Cybern.-Part A: Syst. Hum.
  doi: 10.1109/TSMCA.2011.2116004
– volume: 4
  issue: 8
  year: 2009
  ident: 10.1016/j.bspc.2022.104198_b5
  article-title: Recognition of handwriting from electromyography
  publication-title: PLoS One
  doi: 10.1371/journal.pone.0006791
– start-page: 47
  year: 2016
  ident: 10.1016/j.bspc.2022.104198_b29
  article-title: Extracting muscle synergy patterns from EMG data using autoencoders
– volume: 8
  start-page: 1126
  issue: 7
  year: 2018
  ident: 10.1016/j.bspc.2022.104198_b30
  article-title: Stacked sparse autoencoders for EMG-based classification of hand motions: A comparative multi day analyses between surface and intramuscular EMG
  publication-title: Appl. Sci.
  doi: 10.3390/app8071126
– volume: 15
  start-page: 1
  issue: 1
  year: 2018
  ident: 10.1016/j.bspc.2022.104198_b31
  article-title: Online mapping of EMG signals into kinematics by autoencoding
  publication-title: J. Neuroeng. Rehabil.
  doi: 10.1186/s12984-018-0363-1
– volume: 17
  start-page: 5432
  issue: 5
  year: 2020
  ident: 10.1016/j.bspc.2022.104198_b26
  article-title: Multi-stroke handwriting character recognition based on sEMG using convolutional-recurrent neural networks
  publication-title: Math. Biosci. Eng.
  doi: 10.3934/mbe.2020293
– volume: 60
  start-page: 1179
  issue: 4
  year: 1986
  ident: 10.1016/j.bspc.2022.104198_b35
  article-title: Intramuscular and surface electromyogram changes during muscle fatigue
  publication-title: J. Appl. Physiol.
  doi: 10.1152/jappl.1986.60.4.1179
– volume: 26
  start-page: 692
  issue: 5
  year: 2021
  ident: 10.1016/j.bspc.2022.104198_b40
  article-title: Inertial motion tracking on mobile and wearable devices: Recent advancements and challenges
  publication-title: Tsinghua Sci. Technol.
  doi: 10.26599/TST.2021.9010017
– year: 2015
  ident: 10.1016/j.bspc.2022.104198_b42
– volume: 67
  start-page: 39
  year: 2016
  ident: 10.1016/j.bspc.2022.104198_b15
  article-title: Evaluation of handwriting kinematics and pressure for differential diagnosis of Parkinson’s disease
  publication-title: Artif. Intell. Med.
  doi: 10.1016/j.artmed.2016.01.004
– volume: 10
  start-page: 1
  issue: 2
  year: 2002
  ident: 10.1016/j.bspc.2022.104198_b43
  article-title: Surface electromyography: Detection and recording
  publication-title: DelSys Incorporated
– year: 2021
  ident: 10.1016/j.bspc.2022.104198_b61
– start-page: 437
  year: 2012
  ident: 10.1016/j.bspc.2022.104198_b63
  article-title: Practical recommendations for gradient-based training of deep architectures
SSID ssj0048714
Score 2.392731
Snippet Despite rapid advancements in technology, handwritten characters still hold significant roles in various fields, including education, communication, biometric...
SourceID crossref
elsevier
SourceType Enrichment Source
Index Database
Publisher
StartPage 104198
SubjectTerms Accelerometers
Biomedical signal processing
Deep learning
Electromyogram
Gyroscopes
Title Leveraging deep feature learning for wearable sensors based handwritten character recognition
URI https://dx.doi.org/10.1016/j.bspc.2022.104198
Volume 80
WOSCitedRecordID wos000875634300007&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
journalDatabaseRights – providerCode: PRVESC
  databaseName: Elsevier SD Freedom Collection Journals 2021
  customDbUrl:
  eissn: 1746-8108
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0048714
  issn: 1746-8094
  databaseCode: AIEXJ
  dateStart: 20060101
  isFulltext: true
  titleUrlDefault: https://www.sciencedirect.com
  providerName: Elsevier
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1Lb9QwELag5QCHqjyqFijygVuUyok3TnysUCtaoQqJIu0FRY4zodtCGm2W7v58xq9sKFDRA5do10psK_NpPDOZmY-QtxIA0jrNYqUBHRSuRKwmrIkVnj5oHWdZBYUlm8jPzorpVH70oeze0gnkbVusVrL7r6LGMRS2KZ29h7iHSXEAf6PQ8Ypix-s_Cf4D4JYd91AN0EUN2N6dgR_C5U0u8Y8tmurRjTV8O-Y0qyMTRl_OZws0pE1JsGvlHA1JRl6E4Ruwrdx3ZZWzr8aq7VzVQah79GnwQxAHx20Q59OF6nGlq8jmd48SDHCfNzij1VffTdRiHJNIeUhjHtRoPjFtjh19cdCzjrHJK0r0AhNHP_2bDnfhhMuDqu9Mj8k0PVjf_GvD7FsH2ZBeGDLXLkszR2nmKN0cD8lmmmcSNfjm4cnR9DQc2ui22Tbww8Z9fZVLBby9kz_bMCO75HybbHmHgh46IDwlD6B9Rp6M2kw-J1_WkKAGEtRDggZIUIQEDZCgHhLUQoKOIEEHSNARJF6Qz8dH5-_ex55WI9acsUVcpSLFxRJgTaG5hkZILgSrlKyYkOi_N1wZS5_XhVR5xRoOiVZFLWUlmS443yEb7XULu4QmDQhRi6yutLG7C8OlgKdrxgAtyyaHPZKEF1Vq33PeUJ98K_8uoj0SDc90ruPKnXdn4f2X3mZ0tmCJcLrjuZf3WuUVebyG-WuysZj_gH3ySN8sZv38jcfST6MkkX4
linkProvider Elsevier
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Leveraging+deep+feature+learning+for+wearable+sensors+based+handwritten+character+recognition&rft.jtitle=Biomedical+signal+processing+and+control&rft.au=Singh%2C+Shashank+Kumar&rft.au=Chaturvedi%2C+Amrita&rft.date=2023-02-01&rft.issn=1746-8094&rft.volume=80&rft.spage=104198&rft_id=info:doi/10.1016%2Fj.bspc.2022.104198&rft.externalDBID=n%2Fa&rft.externalDocID=10_1016_j_bspc_2022_104198
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1746-8094&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1746-8094&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1746-8094&client=summon