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Yu RWL, Chan AHS. Effects of player-video game interaction on the mental effort of older adults with the use of electroencephalography and NASA-TLX. Arch Gerontol Geriatr 2024; 124:105442. [PMID: 38676979 DOI: 10.1016/j.archger.2024.105442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2022] [Revised: 04/04/2024] [Accepted: 04/08/2024] [Indexed: 04/29/2024]
Abstract
While player-video game interaction appears to affect older adults in gaming, there is limited knowledge regarding the cognitive demands associated with the anticipation of performing a button press, specifically focusing on the input and game elements relation (I/E relation) in game environments. The study aims to investigate the effects of lateral and rotational displacement amplitudes of game elements, triggered by a single button-press, on the cognitive effort of older adults. Both subjective and objective measurement methods were employed to assess these effects. A total of 48 older adults participated in three casual video game tasks encompassing lateral and rotational displacements at varying I/E relations (low, medium, and high). Results obtained from the NASA Task Load Index and electroencephalography (EEG) measurements revealed significant differences between the I/E relations. Specifically, the subjective rating of cognitive demand among older players was significantly impacted by a small rotation angle associated with a button press, leading to increased mental, physical, and temporal demands, along with decreased performance. Surprisingly, the analysis of EEG data, particularly the theta-alpha ratio, revealed significant interaction effects of I/E relations, button press type, and game type on the cognitive demand required during gameplay. These findings offer practical implications and point towards future avenues for developing player-video game interactions that are more cognitively friendly for older players in gaming environments.
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Affiliation(s)
- R W L Yu
- Department of Systems Engineering, City University of Hong Kong, Hong Kong, China.
| | - A H S Chan
- Department of Systems Engineering, City University of Hong Kong, Hong Kong, China; Shenzhen Research Institute, City University of Hong Kong, Shenzhen, China
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2
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Rajaraman RR, Smith RJ, Oana S, Daida A, Shrey DW, Nariai H, Lopour BA, Hussain SA. Computational EEG attributes predict response to therapy for epileptic spasms. Clin Neurophysiol 2024; 163:39-46. [PMID: 38703698 DOI: 10.1016/j.clinph.2024.03.035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 03/10/2024] [Accepted: 03/28/2024] [Indexed: 05/06/2024]
Abstract
OBJECTIVE We set out to evaluate whether response to treatment for epileptic spasms is associated with specific candidate computational EEG biomarkers, independent of clinical attributes. METHODS We identified 50 children with epileptic spasms, with pre- and post-treatment overnight video-EEG. After EEG samples were preprocessed in an automated fashion to remove artifacts, we calculated amplitude, power spectrum, functional connectivity, entropy, and long-range temporal correlations (LRTCs). To evaluate the extent to which each feature is independently associated with response and relapse, we conducted logistic and proportional hazards regression, respectively. RESULTS After statistical adjustment for the duration of epileptic spasms prior to treatment, we observed an association between response and stronger baseline and post-treatment LRTCs (P = 0.042 and P = 0.004, respectively), and higher post-treatment entropy (P = 0.003). On an exploratory basis, freedom from relapse was associated with stronger post-treatment LRTCs (P = 0.006) and higher post-treatment entropy (P = 0.044). CONCLUSION This study suggests that multiple EEG features-especially LRTCs and entropy-may predict response and relapse. SIGNIFICANCE This study represents a step toward a more precise approach to measure and predict response to treatment for epileptic spasms.
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Affiliation(s)
- Rajsekar R Rajaraman
- Division of Pediatric Neurology, UCLA Mattel Children's Hospital and University of California, Los Angeles, Los Angeles, CA, USA
| | - Rachel J Smith
- Department of Electrical and Computer Engineering, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Shingo Oana
- Division of Pediatric Neurology, UCLA Mattel Children's Hospital and University of California, Los Angeles, Los Angeles, CA, USA
| | - Atsuro Daida
- Division of Pediatric Neurology, UCLA Mattel Children's Hospital and University of California, Los Angeles, Los Angeles, CA, USA
| | - Daniel W Shrey
- Division of Pediatric Neurology, University of California, Irvine, Irvine, CA, USA; Department of Neurology, Children's Hospital of Orange County, Orange, CA, USA
| | - Hiroki Nariai
- Division of Pediatric Neurology, UCLA Mattel Children's Hospital and University of California, Los Angeles, Los Angeles, CA, USA
| | - Beth A Lopour
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, USA
| | - Shaun A Hussain
- Division of Pediatric Neurology, UCLA Mattel Children's Hospital and University of California, Los Angeles, Los Angeles, CA, USA.
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3
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Deckard E, Sathe R, Tabibzadeh D, Terango A, Groves A, Rajaraman RR, Nariai H, Hussain SA. Epileptic spasms relapse is associated with response latency but not conventional attributes of post-treatment EEG. Epilepsia Open 2024; 9:1034-1041. [PMID: 38588009 PMCID: PMC11145600 DOI: 10.1002/epi4.12931] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Revised: 02/06/2024] [Accepted: 03/09/2024] [Indexed: 04/10/2024] Open
Abstract
OBJECTIVE Relapse of epileptic spasms after initial treatment of infantile epileptic spasms syndrome (IESS) is common. However, past studies of small cohorts have inconsistently linked relapse risk to etiology, treatment modality, and EEG features upon response. Using a large single-center IESS cohort, we set out to quantify the risk of epileptic spasms relapse and identify specific risk factors. METHODS We identified all children with epileptic spasms at our center using a clinical EEG database. Using the electronic medical record, we confirmed IESS syndrome classification and ascertained treatment, response, time to relapse, etiology, EEG features, and other demographic factors. Relapse-free survival analysis was carried out using Cox proportional hazards regression. RESULTS Among 599 children with IESS, 197 specifically responded to hormonal therapy and/or vigabatrin (as opposed to surgery or other second-line treatments). In this study, 41 (21%) subjects exhibited relapse of epileptic spasms within 12 months of response. Longer duration of IESS prior to response (>3 months) was strongly associated with shorter latency to relapse (hazard ratio = 3.11; 95% CI 1.59-6.10; p = 0.001). Relapse was not associated with etiology, developmental status, or any post-treatment EEG feature. SIGNIFICANCE This study suggests that long duration of IESS before response is the single largest clinical predictor of relapse risk, and therefore underscores the importance of prompt and successful initial treatment. Further study is needed to evaluate candidate biomarkers of epileptic spasms relapse and identify treatments to mitigate this risk. PLAIN LANGUAGE SUMMARY Relapse of infantile spasms is common after initially successful treatment. With study of a large group of children with infantile spasms, we determined that relapse is linked to long duration of infantile spasms. In contrast, relapse was not associated with the cause of infantile spasms, developmental measures, or EEG features at the time of initial response. Further study is needed to identify tools to predict impending relapse of infantile spasms.
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Affiliation(s)
- Emmi Deckard
- Department of PediatricsDivision of NeurologyUniversity of California Los Angeles and UCLA Mattel Children's HospitalCaliforniaLos AngelesUSA
| | - Rujuta Sathe
- Department of PediatricsDivision of NeurologyUniversity of California Los Angeles and UCLA Mattel Children's HospitalCaliforniaLos AngelesUSA
| | - David Tabibzadeh
- Department of PediatricsDivision of NeurologyUniversity of California Los Angeles and UCLA Mattel Children's HospitalCaliforniaLos AngelesUSA
| | - Aria Terango
- Department of PediatricsDivision of NeurologyUniversity of California Los Angeles and UCLA Mattel Children's HospitalCaliforniaLos AngelesUSA
| | - Aran Groves
- Department of PediatricsDivision of NeurologyUniversity of California Los Angeles and UCLA Mattel Children's HospitalCaliforniaLos AngelesUSA
| | - Rajsekar R. Rajaraman
- Department of PediatricsDivision of NeurologyUniversity of California Los Angeles and UCLA Mattel Children's HospitalCaliforniaLos AngelesUSA
| | - Hiroki Nariai
- Department of PediatricsDivision of NeurologyUniversity of California Los Angeles and UCLA Mattel Children's HospitalCaliforniaLos AngelesUSA
| | - Shaun A. Hussain
- Department of PediatricsDivision of NeurologyUniversity of California Los Angeles and UCLA Mattel Children's HospitalCaliforniaLos AngelesUSA
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Miyakoshi M. Artifact subspace reconstruction: a candidate for a dream solution for EEG studies, sleep or awake. Sleep 2023; 46:zsad241. [PMID: 37715954 PMCID: PMC10710985 DOI: 10.1093/sleep/zsad241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Indexed: 09/18/2023] Open
Affiliation(s)
- Makoto Miyakoshi
- Division of Child and Adolescent Psychiatry, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA
- Department of Psychiatry, University of Cincinnati College of Medicine, Cincinnati, OH, USA
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Somervail R, Cataldi J, Stephan AM, Siclari F, Iannetti GD. Dusk2Dawn: an EEGLAB plugin for automatic cleaning of whole-night sleep electroencephalogram using Artifact Subspace Reconstruction. Sleep 2023; 46:zsad208. [PMID: 37542730 DOI: 10.1093/sleep/zsad208] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Revised: 07/20/2023] [Indexed: 08/07/2023] Open
Abstract
Whole-night sleep electroencephalogram (EEG) is plagued by several types of large-amplitude artifacts. Common approaches to remove them are fraught with issues: channel interpolation, rejection of noisy intervals, and independent component analysis are time-consuming, rely on subjective user decisions, and result in signal loss. Artifact Subspace Reconstruction (ASR) is an increasingly popular approach to rapidly and automatically clean wake EEG data. Indeed, ASR adaptively removes large-amplitude artifacts regardless of their scalp topography or consistency throughout the recording. This makes ASR, at least in theory, a highly-promising tool to clean whole-night EEG. However, ASR crucially relies on calibration against a subset of relatively clean "baseline" data. This is problematic when the baseline changes substantially over time, as in whole-night EEG data. Here we tackled this issue and, for the first time, validated ASR for cleaning sleep EEG. We demonstrate that ASR applied out-of-the-box, with the parameters recommended for wake EEG, results in the dramatic removal of slow waves. We also provide an appropriate procedure to use ASR for automatic and rapid cleaning of whole-night sleep EEG data or any long EEG recording. Our procedure is freely available in Dusk2Dawn, an open-source plugin for EEGLAB.
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Affiliation(s)
- Richard Somervail
- Neuroscience and Behaviour Laboratory, Italian Institute of Technology (IIT), Rome, Italy
- Department of Neuroscience Physiology and Pharmacology, University College London (UCL), London, UK
| | - Jacinthe Cataldi
- Centre d'Investigation et de Recherche sur le Sommeil, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland
- The Sense Innovation and Research Center, Lausanne and Sion, Switzerland
| | - Aurélie M Stephan
- Centre d'Investigation et de Recherche sur le Sommeil, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland
- The Sense Innovation and Research Center, Lausanne and Sion, Switzerland
- Netherlands Institute for Neuroscience, Amsterdam, The Netherlands
| | - Francesca Siclari
- Centre d'Investigation et de Recherche sur le Sommeil, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland
- The Sense Innovation and Research Center, Lausanne and Sion, Switzerland
- Netherlands Institute for Neuroscience, Amsterdam, The Netherlands
| | - Gian Domenico Iannetti
- Neuroscience and Behaviour Laboratory, Italian Institute of Technology (IIT), Rome, Italy
- Department of Neuroscience Physiology and Pharmacology, University College London (UCL), London, UK
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Wan L, Zhang CT, Zhu G, Chen J, Shi XY, Wang J, Zou LP, Zhang B, Shi WB, Yeh CH, Yang G. Integration of multiscale entropy and BASED scale of electroencephalography after adrenocorticotropic hormone therapy predict relapse of infantile spasms. World J Pediatr 2022; 18:761-770. [PMID: 35906344 DOI: 10.1007/s12519-022-00583-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2022] [Accepted: 06/12/2022] [Indexed: 11/28/2022]
Abstract
BACKGROUND Even though adrenocorticotropic hormone (ACTH) demonstrated powerful efficacy in the initially successful treatment of infantile spasms (IS), nearly half of patients have experienced a relapse. We sought to investigate whether features of electroencephalogram (EEG) predict relapse in those IS patients without structural brain abnormalities. METHODS We retrospectively reviewed data from children with IS who achieved initial response after ACTH treatment, along with EEG recorded within the last two days of treatment. The recurrence of epileptic spasms following treatment was tracked for 12 months. Subjects were categorized as either non-relapse or relapse groups. General clinical and EEG recordings were collected, burden of amplitudes and epileptiform discharges (BASED) score and multiscale entropy (MSE) were carefully explored for cross-group comparisons. RESULTS Forty-one patients were enrolled in the study, of which 26 (63.4%) experienced a relapse. The BASED score was significantly higher in the relapse group. MSE in the non-relapse group was significantly lower than the relapse group in the γ band but higher in the lower frequency range (δ, θ, α). Sensitivity and specificity were 85.71% and 92.31%, respectively, when combining MSE in the δ/γ frequency of the occipital region, plus BASED score were used to distinguish relapse from non-relapse groups. CONCLUSIONS BASED score and MSE of EEG after ACTH treatment could be used to predict relapse for IS patients without brain structural abnormalities. Patients with BASED score ≥ 3, MSE increased in higher frequency, and decreased in lower frequency had a high risk of relapse.
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Affiliation(s)
- Lin Wan
- Senior Department of Pediatrics, Chinese PLA General Hospital, Beijing, 100000, China.,Department of Pediatrics, the First Medical Centre, Chinese PLA General Hospital, Beijing, China.,Medical School of Chinese People's Liberation Army, Beijing, China
| | - Chu-Ting Zhang
- School of Information and Electronics, Beijing Institute of Technology, Beijing, 100081, China
| | - Gang Zhu
- Senior Department of Pediatrics, Chinese PLA General Hospital, Beijing, 100000, China.,Department of Pediatrics, the First Medical Centre, Chinese PLA General Hospital, Beijing, China.,Medical School of Chinese People's Liberation Army, Beijing, China
| | - Jian Chen
- Senior Department of Pediatrics, Chinese PLA General Hospital, Beijing, 100000, China.,Department of Pediatrics, the First Medical Centre, Chinese PLA General Hospital, Beijing, China
| | - Xiu-Yu Shi
- Senior Department of Pediatrics, Chinese PLA General Hospital, Beijing, 100000, China.,Department of Pediatrics, the First Medical Centre, Chinese PLA General Hospital, Beijing, China.,Medical School of Chinese People's Liberation Army, Beijing, China.,The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China
| | - Jing Wang
- Senior Department of Pediatrics, Chinese PLA General Hospital, Beijing, 100000, China.,Department of Pediatrics, the First Medical Centre, Chinese PLA General Hospital, Beijing, China
| | - Li-Ping Zou
- Senior Department of Pediatrics, Chinese PLA General Hospital, Beijing, 100000, China.,Department of Pediatrics, the First Medical Centre, Chinese PLA General Hospital, Beijing, China.,Medical School of Chinese People's Liberation Army, Beijing, China.,The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China
| | - Bo Zhang
- Department of Neurology and ICCTR Biostatistics and Research Design Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Wen-Bin Shi
- School of Information and Electronics, Beijing Institute of Technology, Beijing, 100081, China
| | - Chien-Hung Yeh
- School of Information and Electronics, Beijing Institute of Technology, Beijing, 100081, China.
| | - Guang Yang
- Senior Department of Pediatrics, Chinese PLA General Hospital, Beijing, 100000, China. .,Department of Pediatrics, the First Medical Centre, Chinese PLA General Hospital, Beijing, China. .,Medical School of Chinese People's Liberation Army, Beijing, China. .,The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China.
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Romero Milà B, Remakanthakurup Sindhu K, Mytinger JR, Shrey DW, Lopour BA. EEG biomarkers for the diagnosis and treatment of infantile spasms. Front Neurol 2022; 13:960454. [PMID: 35968272 PMCID: PMC9366674 DOI: 10.3389/fneur.2022.960454] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 06/28/2022] [Indexed: 11/13/2022] Open
Abstract
Early diagnosis and treatment are critical for young children with infantile spasms (IS), as this maximizes the possibility of the best possible child-specific outcome. However, there are major barriers to achieving this, including high rates of misdiagnosis or failure to recognize the seizures, medication failure, and relapse. There are currently no validated tools to aid clinicians in assessing objective diagnostic criteria, predicting or measuring medication response, or predicting the likelihood of relapse. However, the pivotal role of EEG in the clinical management of IS has prompted many recent studies of potential EEG biomarkers of the disease. These include both visual EEG biomarkers based on human visual interpretation of the EEG and computational EEG biomarkers in which computers calculate quantitative features of the EEG. Here, we review the literature on both types of biomarkers, organized based on the application (diagnosis, treatment response, prediction, etc.). Visual biomarkers include the assessment of hypsarrhythmia, epileptiform discharges, fast oscillations, and the Burden of AmplitudeS and Epileptiform Discharges (BASED) score. Computational markers include EEG amplitude and power spectrum, entropy, functional connectivity, high frequency oscillations (HFOs), long-range temporal correlations, and phase-amplitude coupling. We also introduce each of the computational measures and provide representative examples. Finally, we highlight remaining gaps in the literature, describe practical guidelines for future biomarker discovery and validation studies, and discuss remaining roadblocks to clinical implementation, with the goal of facilitating future work in this critical area.
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Affiliation(s)
- Blanca Romero Milà
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, United States
- Department of Electronics and Biomedical Engineering, Universitat de Barcelona, Barcelona, Spain
| | | | - John R. Mytinger
- Division of Pediatric Neurology, Department of Pediatrics, Nationwide Children's Hospital, The Ohio State University, Columbus, OH, United States
| | - Daniel W. Shrey
- Division of Neurology, Children's Hospital Orange County, Orange, CA, United States
- Department of Pediatrics, University of California, Irvine, Irvine, CA, United States
| | - Beth A. Lopour
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, United States
- *Correspondence: Beth A. Lopour
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