Architecture for Groupware Oriented to Collaborative Medical Activities in the Rehabilitation of Strokes
Authors: 
Sofía Isabel Fernández Gregorio, Luis G. Montané-Jiménez, Carmen Mezura Godoy, Viviana Yarel Rosales-MoralesAuthors Info & Claims
Pages 643 - 656
Abstract
Abstract
When a person suffers a stroke, they require rehabilitation to recover from the consequences caused by this event. In order to carry out the rehabilitation, a multidisciplinary team of specialists intervenes, providing care from diverse areas such as neurology, nutrition, psychology, and physiotherapy. In the rehabilitation process, physicians interact with medical computing software and devices. The interactions represent medical activities that follow rehabilitation. However, there is no clear conception of how specialists coordinate to carry out medical activities. There are no specific communication channels that allow multidisciplinary collaboration for complete rehabilitation. This paper presents a systematic review of the state of the art that addresses this problem. On the other hand, a collaborative software architecture is proposed to support this area, which allows the monitoring medical activities from human-computer multimodal interactions. The architecture is composed of 3 layers: (1) to perceive the interactions and to monitor the activities, (2) to control the multidisciplinary access and share the information, and (3) to analyze and evaluate the execution of the multidisciplinary activities. Evaluating how the activities are carried out will help the physicians make decisions regarding the execution of the treatment plan. Therefore, we propose an activities representation diagram that facilitates this evaluation. Finally, we developed a prototype with a user-centered design that perceives human-computer interactions supported by the architecture.
References
[1]
Interaccion, Revista digital de AIPO, Asociacion Interccion Persona-Ordenador. https://revista.aipo.es/index.php/INTERACCION/CFP-multimodal-HCI. Accessed Apr. 25, 2022.
[2]
Lukin V.N., Dzyubenko A.L., and Chechikov Y.B. Approaches to user interface development Program. Comput. Softw. 2020 46 316-323
[3]
Alessandro, L., Olmos, L.E., Bonamico, L., Muzio, D.M., Ahumada, M.H., Russo, M.J., Allegri, R.F., Gia-nella, M.G., Campora, H., Delorme, R., Vescovo, M.E., Lado, V., Mastroberti, L.R., Butus, A., Galluzzi, H.D., Décima, G., and Ameriso, S.F., Rehabilitación multidisciplinaria para pacientes adultos con accidente cerebrovascular, Medicina (B. Aires), n.d., vol. 80, pp. 54–68.
[4]
Gregorio, S.I.F. and Montané-Jiménez, L.G., Towards the improvement of computer-assisted medical activities for stroke rehabilitation, Proc. 10th Int. Conf. in Software Engineering Research and Innovation (CONISOFT), Puebla, Oct. 2022, pp. 102–111.
[5]
Hayyolalam V. and Kazem A.A.P. A systematic literature review on QoS-aware service composition and selection in cloud environment J. Netw. Comput. Appl. 2018 110 52-74
[6]
Obana M., Furuya J., Matsubara C., Tohara H., Inaji M., Miki K., Numasawa Y., Minakuchi S., and Maehara T. Effect of a collaborative transdisciplinary team approach on oral health status in acute stroke patients J. Oral Rehabil. 2019 46 1170-1176
[7]
Pristipino, C., Anzola, G.P., Ballerini, L., Bartorelli, A., Cecconi, M., Chessa, M., Donti, A., Gaspardone, A., Neri, G., Onorato, E., Palareti, G., Rakar, S., Rigatelli, G., Santoro, G., Toni, D., Ussia, G.P., and Violini, R., Management of patients with patent foramen ovale and cryptogenic stroke: A collaborative, multidisciplinary, position paper, Catheter. Cardiovasc. Interv., 2013, vol. 82, no. 1,.
[8]
Watson T., Tiu J., and Clissold B. Addressing inequity in acute stroke care requires attention to each component of regional workflow Med. J. Aust. 2020 212 8-10
[9]
Tiu, J., Watson, T., and Clissold, B., Mechanical thrombectomy for emergent large vessel occlusion: an Australian primary stroke centre workflow analysis, Int. Med. J., 2021, vol. 51, no. 6, pp. 905–909.
[10]
Alonso de Leciñana M., Fuentes B., Ximénez-Carrillo A., Vivancos J., Masjuan J., Gil-Nuñez A., Martínez-Sánchez P., Zapata-Wainberg G., Cruz-Culebras A., García-Pastor A., Díaz-Otero F., Fandiño E., Frutos R., Caniego J.L., Méndez J.C., Fernández-Prieto A., Bárcena-Ruiz E., and Díez-Tejedor E. A collaborative system for endovascular treatment of acute ischaemic stroke: the Madrid Stroke Network experience Eur. J. Neurol. 2016 23 297-303
[11]
Macisaac R.L., Khatri P., Bendszus M., Bracard S., Broderick J., Campbell B., Ciccone A., Dávalos A., Davis S.M., Demchuk A., Diener H.C., Dippel D., Donnan G.A., Fiehler J., Fiorella D., Goyal M., Hacke W., Hill M.D., Jahan R., and Lees K.R. A collaborative sequential meta-analysis of individual patient data from randomized trials of endovascular therapy and tPA vs. tPA alone for acute ischemic stroke: ThRombEctomy And tPA (TREAT) analysis: statistical analysis plan for a sequential meta-anal Int. J. Stroke 2015 10 136-144
[12]
Chowdhury S.Z., Baskar P.S., and Bhaskar S. Effect of prehospital workflow optimization on treatment delays and clinical outcomes in acute ischemic stroke: a systematic review and meta-analysis Acad. Emerg. Med. 2021 28 781-801
[13]
Santanna Baskar P., Cordato D., Wardman D., and Bhaskar S. In-hospital acute stroke workflow in acute stroke – systems-based approaches Acta Neurol. Scand. 2021 143 111-120
[14]
Rogers, H., Madathil, K.C., Joseph, A., Holmstedt, C., Qanungo, S., McNeese, N., Morris, T., Holden, R.J., and McElligott, J.T., An exploratory study investigating the barriers, facilitators, and demands affecting caregivers in a telemedicine integrated ambulance-based setting for stroke care, Appl. Ergon., 2021, vol. 97, p. 103537.
[15]
Daemen, E.M.L., Flinsenberg, I.C.M., van Loenen, E.J., Cuppen, R.P.G., and Rajae-Joordens, R.J.E., Adaptive daily rhythm atmospheres for stroke patients: a staff evaluation, Proc. 7th Int. Conf. on Pervasive Computing Technologies for Healthcare and Workshops, PervasiveHealth 2013, Venice, 2013, pp. 121–128.
[16]
Grigoriev O.G., Kobrinskii B.A., Osipov G.S., Molodchenkov A.I., and Smirnov I.V. Health management system knowledge base for formation and support of a preventive measures plan Procedia Comput. Sci. 2018 145 238-241
[17]
Esensoy A.V. and Carter M.W. High-fidelity whole-system patient flow modeling to assess health care transformation policies Eur. J. Oper. Res. 2018 266 221-237
[18]
Ferrante S., Bonacina S., and Pinciroli F. Modeling stroke rehabilitation processes using the Unified Modeling Language (UML) Comput. Biol. Med. 2013 43 1390-1401
[19]
Yang, Y., Xu, H., Qi, B., Niu, X., Li, M., and Zhao, D., Stroke screening data modeling based on openEHR and NINDS Stroke CDE, Proc. IEEE Int. Conf. on Bioinformatics and Biomedicine, BIBM 2020, 2020, pp. 2147–2152.
[20]
Wantaka, C., Kitidumrongsuk, P., Soontornpipit, P., and Sillabutra, J., Design and development of data model for stroke FAST track system, Proc. 6th Int. Electrical Engineering Congress IEECON 2018, Krabi, 2018.
[21]
Chang T.M., Kao H.Y., Wu J.H., and Su Y.F. Improving physicians’ performance with a stroke CDSS: a cognitive fit design approach Comput. Human Behav. 2016 54 577-586
[22]
Gibson O.J., Balami J.S., Pope G.A., Tarassenko L., and Reckless I.P. “Stroke Nav”: a wireless data collection and review system to support stroke care delivery Comput. Methods Programs Biomed. 2012 108 338-345
[23]
Tang, Z., Lawson, S., Messing, D., Guo, J., Smith, T., and Feng, J., Collaborative rehabilitation support system: a comprehensive solution for everyday rehab, Proc. IEEE Int. Symp. on Multimedia, ISM 2015”, Miami, 2015, pp. 61–64.
[24]
Sun, M., Dai, D., Wu, X., Wang, S., Zang, T., and Xu, X., SS4CSHC: a Services System for the Collaboration in Stroke Healthcare Cycle, Proc. Int. Conference on Service Science, ICSS-2016, ChongQing, 2016, pp. 174–180.
[25]
Li S. and Manogaran G. Design and implementation of networked collaborative service system for brain stroke prevention and first aid IEEE Access 2019 7 14825-14836
[26]
Ilieva, R.Y. and Damyanov, V., NextGen hightech solutions to improve the qol in cerebral stroke consequences, Proc. 10th National Conf. with International Participation, Electronica 2019, Sofia, 2019.
[27]
Park E., Kim J.H., Nam H.S., and Chang H.J. Requirement analysis and implementation of smart emergency medical services IEEE Access 2018 6 42022-42029
[28]
Wang, Y., When music, information technology, and medicine meet, Proc. 2nd Int. ACM Workshop on Music Information Retrieval with User-Centered and Multimodal Strategies, Co-Located with ACM Multimedia 2012 MIRUM 2012, Nara, 2012, pp. 43–44.
[29]
Ramesh, V., Kim, S., Nguyen, H.A., Agrawal, K., Meyer, B.C., and Weibel, N., Developing aids to assist acute stroke diagnosis, Proc. Conf. on Human Factors in Computing Systems, 2020.
[30]
Tsoupikova, D., Triandafilou, K., Solanki, S., Barry, A., Preuss, F., and Kamper, D., Real-time diagnostic data in multi-user virtual reality post-stroke therapy, Proc. SIGGRAPH ASIA 2016 VR Showcase”, Macau, 2016.
[31]
Virbitskaite I.B. and Dubtsov R.S. Semantic domains of timed event structures Program. Comput. Softw. 2008 34 125-137
[32]
Zhuklinets I.A. and Khotimsky D.A. Logical time in distributed software systems Program. Comput. Softw. 2002 28 174-184
Index Terms
- Architecture for Groupware Oriented to Collaborative Medical Activities in the Rehabilitation of Strokes
Index terms have been assigned to the content through auto-classification.
Recommendations
An Architecture for Ambient Assisted Living and Health Environments
IWANN '09: Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part II: Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted LivingThe hospital and home are ancillary places in the life of elderly people, people with high risk of health problems or patients who have had recently an operation. We propose an architecture for Ambient Assisted Living (AAL) and health environments that ...
Single display groupware
CHI EA '97: CHI '97 Extended Abstracts on Human Factors in Computing SystemsFace-to-face collaboration of small groups is one of the most common forms of group work, yet group-aware computer support for this type of collaboration is limited. My research examines the effectiveness of Single Display Groupware (SDG), computer ...
A groupware system to support collaborative programming: Design and experiences
The advances in network and collaboration technologies enable the creation of powerful environments for collaborative programming. One such environment is COLLECE, a groupware system to support collaborative edition, compilation and execution of ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
© Pleiades Publishing, Ltd. 2023. ISSN 0361-7688, Programming and Computer Software, 2023, Vol. 49, No. 8, pp. 643–656. © Pleiades Publishing, Ltd., 2023.
Publisher
Plenum Press
United States
Publication History
Published: 24 January 2024
Accepted: 02 August 2023
Revision received: 12 July 2023
Received: 14 June 2023
Author Tags
Qualifiers
- Research-article
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 0Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0
Reflects downloads up to 01 Jan 2025