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Bioengineering
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Adaptive Neurostimulation: Innovative Strategies for Stimulation
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Adaptive Neurostimulation: Innovative Strategies for Stimulation

A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biosignal Processing".

Deadline for manuscript submissions: 31 October 2025 | Viewed by 11097

Special Issue Editor

Dr. Luca Mesin

E-Mail Website
Guest Editor
Department of Electronics and Telecommunications, Polytechnic University of Turin, Turin, Italy
Interests: biomedical signal and image processing and classification; biophysical modelling; clinical studies; mathematical biology and physiology; noninvasive monitoring of the volemic status of patients; nonlinear biomedical signal processing; optimal non-uniform down-sampling; systems for human–machine interaction
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleague,

Over the last two decades, neurostimulation has solicited solid interest among the scientific community. Defined as a treatment involving either one or multiple stimulations (e.g., auditive, mechanical, or electrical), this technique finds several medical applications. Treating epilepsy, psychiatric disorders, and chronic pain are just a few examples.

Even though neurostimulation is mostly associated with transcranial magnetic stimulation (TMS), vagus nerve stimulation (VNS), and deep brain stimulation (DBS), researchers are working on new treatments that exploit other sources to adapt the stimuli in a closed-loop system. For this purpose, biological signals such as electroencephalogram (EEG), pupillogram, electrocardiogram (ECG), and breathing rhythm can be used.

Because most of the neurostimulation techniques are based on fixed stimulation, posing a limitation to personalized treatments, this Special Issue aims to explore innovative solutions based on closed-loop approaches that exploit physiological parameters.

Topics of interest include, but are not limited to, the following:

  • Real-time and offline neurostimulation solutions;
  • Techniques based on artificial intelligence (AI) algorithms;
  • Multi-sensor approaches to optimize the closed-loop strategy;
  • Solutions based on physiological data acquired through wearable devices;
  • Therapeutic applications.

Dr. Luca Mesin
Guest Editor

Matteo Raggi
Guest Editor Assistant
Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy
Email: matteo.raggi@polito.it
Website: https://www.polito.it/personale?p=098271
Interests: biomedical devices and applications

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Bioengineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • neurostimulation
  • closed-loop stimulation
  • adaptive stimulation
  • sustained attention
  • working memory
  • meditation
  • relaxation
  • stress
  • mindfulness
  • epilepsy
  • psychiatric disorders
  • ADHD
  • transcranial direct current stimulation
  • transcranial alternating current stimulation
  • binaural beats
  • light pulse stimulation
  • EEG
  • ECG
  • pupillogram
  • breath monitoring
  • real time processing
  • EEG rhythms
  • complexity
  • entropy
  • heart rate variability

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Published Papers (4 papers)

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Research

20 pages, 368 KiB  
Article
Sensory–Cognitive Profiles in Children with ADHD: Exploring Perceptual–Motor, Auditory, and Oculomotor Function
by Danjela Ibrahimi, Marcos Aviles, Rafael Rojas-Galván and Juvenal Rodríguez Reséndiz
Bioengineering 2025, 12(6), 621; https://doi.org/10.3390/bioengineering12060621 - 7 Jun 2025
Viewed by 1939
Abstract
Objective: This observational cross-sectional study aimed to comprehensively evaluate sensory–cognitive performance in children diagnosed with Attention-Deficit/Hyperactivity Disorder (ADHD), with a focus on auditory processing, visual–perceptual abilities, visual–motor integration, and oculomotor function. The study further examined how hyperactivity, age, and gender may influence these [...] Read more.
Objective: This observational cross-sectional study aimed to comprehensively evaluate sensory–cognitive performance in children diagnosed with Attention-Deficit/Hyperactivity Disorder (ADHD), with a focus on auditory processing, visual–perceptual abilities, visual–motor integration, and oculomotor function. The study further examined how hyperactivity, age, and gender may influence these domains. Methods: A total of 70 non-medicated children with clinically diagnosed ADHD (mean age = 9.1±2.4 years; 67.1% male), all with normal visual acuity, were assessed using four standardized instruments: the Test of Auditory Processing Skills, Third Edition (TAPS-3), the Test of Visual Perceptual Skills, Fourth Edition (TVPS-4), the Beery–Buktenica Developmental Test of Visual–Motor Integration, Sixth Edition (VMI-6), and the Developmental Eye Movement (DEM) Test. Statistical analyses included one sample and independent samples t-tests, one-way ANOVA, and Pearson correlation coefficients. Results: Participants demonstrated significantly above-average performance in auditory processing (TAPS-3: μ=108.4, std=7.8), average visual–perceptual abilities (TVPS-4: μ=100.9, std=7.2), slightly below-average visual–motor integration (VMI-6: μ=97.1, std=9.0), and marked deficits in oculomotor efficiency (DEM ratio: μ=87.3, std=18.1). Statistically significant differences were observed across these domains (t-values ranging from 2.9 to 7.2, p<0.01). Children with hyperactive-impulsive presentations exhibited lower horizontal DEM scores (μ=73.4, std=12.3) compared to inattentive counterparts (μ=82.9, std=16.2; p=0.009). Age and sex influenced specific subtest scores, with boys and children aged 8–9 years achieving higher outcomes in word memory (p=0.042) and visual discrimination (p=0.034), respectively. Moderate correlations were identified between auditory and visual–perceptual skills (r=0.32, p=0.007), and between visual–perceptual and oculomotor performance (r=0.25, p=0.035). Conclusions: The findings from this sample reveal a distinct sensory–cognitive profile in children with ADHD, characterized by relatively preserved auditory processing and pronounced oculomotor deficits. These results underscore the value of a multimodal assessment protocol that includes oculomotor and visual efficiency evaluations. The conclusions pertain specifically to the cohort studied and should not be generalized to all populations with ADHD without further validation. Full article
(This article belongs to the Special Issue Adaptive Neurostimulation: Innovative Strategies for Stimulation)
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25 pages, 5732 KiB  
Article
Analyzing the Impact of Binaural Beats on Anxiety Levels by a New Method Based on Denoised Harmonic Subtraction and Transient Temporal Feature Extraction
by Devika Rankhambe, Bharati Sanjay Ainapure, Bhargav Appasani, Avireni Srinivasulu and Nicu Bizon
Bioengineering 2024, 11(12), 1251; https://doi.org/10.3390/bioengineering11121251 - 10 Dec 2024
Viewed by 1815
Abstract
Anxiety is a widespread mental health issue, and binaural beats have been explored as a potential non-invasive treatment. EEG data reveal changes in neural oscillation and connectivity linked to anxiety reduction; however, harmonics introduced during signal acquisition and processing often distort these findings. [...] Read more.
Anxiety is a widespread mental health issue, and binaural beats have been explored as a potential non-invasive treatment. EEG data reveal changes in neural oscillation and connectivity linked to anxiety reduction; however, harmonics introduced during signal acquisition and processing often distort these findings. Existing methods struggle to effectively reduce harmonics and capture the fine-grained temporal dynamics of EEG signals, leading to inaccurate feature extraction. Hence, a novel Denoised Harmonic Subtraction and Transient Temporal Feature Extraction is proposed to improve the analysis of the impact of binaural beats on anxiety levels. Initially, a novel Wiener Fused Convo Filter is introduced to capture spatial features and eliminate linear noise in EEG signals. Next, an Intrinsic Harmonic Subtraction Network is employed, utilizing the Attentive Weighted Least Mean Square (AW-LMS) algorithm to capture nonlinear summation and resonant coupling effects, effectively eliminating the misinterpretation of brain rhythms. To address the challenge of fine-grained temporal dynamics, an Embedded Transfo XL Recurrent Network is introduced to detect and extract relevant parameters associated with transient events in EEG data. Finally, EEG data undergo harmonic reduction and temporal feature extraction before classification with a cross-correlated Markov Deep Q-Network (DQN). This facilitates anxiety level classification into normal, mild, moderate, and severe categories. The model demonstrated a high accuracy of 95.6%, precision of 90%, sensitivity of 93.2%, and specificity of 96% in classifying anxiety levels, outperforming previous models. This integrated approach enhances EEG signal processing, enabling reliable anxiety classification and offering valuable insights for therapeutic interventions. Full article
(This article belongs to the Special Issue Adaptive Neurostimulation: Innovative Strategies for Stimulation)
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12 pages, 1818 KiB  
Article
Adaptive vs. Conventional Deep Brain Stimulation: One-Year Subthalamic Recordings and Clinical Monitoring in a Patient with Parkinson’s Disease
by Laura Caffi, Luigi M. Romito, Chiara Palmisano, Vanessa Aloia, Mattia Arlotti, Lorenzo Rossi, Sara Marceglia, Alberto Priori, Roberto Eleopra, Vincenzo Levi, Alberto Mazzoni and Ioannis U. Isaias
Bioengineering 2024, 11(10), 990; https://doi.org/10.3390/bioengineering11100990 - 30 Sep 2024
Cited by 3 | Viewed by 2895
Abstract
Conventional DBS (cDBS) for Parkinson’s disease uses constant, predefined stimulation parameters, while the currently available adaptive DBS (aDBS) provides the possibility of adjusting current amplitude with respect to subthalamic activity in the beta band (13–30 Hz). This preliminary study on one patient aims [...] Read more.
Conventional DBS (cDBS) for Parkinson’s disease uses constant, predefined stimulation parameters, while the currently available adaptive DBS (aDBS) provides the possibility of adjusting current amplitude with respect to subthalamic activity in the beta band (13–30 Hz). This preliminary study on one patient aims to describe how these two stimulation modes affect basal ganglia dynamics and, thus, behavior in the long term. We collected clinical data (UPDRS-III and -IV) and subthalamic recordings of one patient with Parkinson’s disease treated for one year with aDBS, alternated with short intervals of cDBS. Moreover, after nine months, the patient discontinued all dopaminergic drugs while keeping aDBS. Clinical benefits of aDBS were superior to those of cDBS, both with and without medications. This improvement was paralleled by larger daily fluctuations of subthalamic beta activity. Moreover, with aDBS, subthalamic beta activity decreased during asleep with respect to awake hours, while it remained stable in cDBS. These preliminary data suggest that aDBS might be more effective than cDBS in preserving the functional role of daily beta fluctuations, thus leading to superior clinical benefit. Our results open new perspectives for a restorative brain network effect of aDBS as a more physiological, bidirectional, brain–computer interface. Full article
(This article belongs to the Special Issue Adaptive Neurostimulation: Innovative Strategies for Stimulation)
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18 pages, 2273 KiB  
Article
Closed-Loop Transcranial Electrical Neurostimulation for Sustained Attention Enhancement: A Pilot Study towards Personalized Intervention Strategies
by Emma Caravati, Federica Barbeni, Giovanni Chiarion, Matteo Raggi and Luca Mesin
Bioengineering 2024, 11(5), 467; https://doi.org/10.3390/bioengineering11050467 - 8 May 2024
Cited by 2 | Viewed by 3351
Abstract
Sustained attention is pivotal for tasks like studying and working for which focus and low distractions are necessary for peak productivity. This study explores the effectiveness of adaptive transcranial direct current stimulation (tDCS) in either the frontal or parietal region to enhance sustained [...] Read more.
Sustained attention is pivotal for tasks like studying and working for which focus and low distractions are necessary for peak productivity. This study explores the effectiveness of adaptive transcranial direct current stimulation (tDCS) in either the frontal or parietal region to enhance sustained attention. The research involved ten healthy university students performing the Continuous Performance Task-AX (AX-CPT) while receiving either frontal or parietal tDCS. The study comprised three phases. First, we acquired the electroencephalography (EEG) signal to identify the most suitable metrics related to attention states. Among different spectral and complexity metrics computed on 3 s epochs of EEG, the Fuzzy Entropy and Multiscale Sample Entropy Index of frontal channels were selected. Secondly, we assessed how tDCS at a fixed 1.0 mA current affects attentional performance. Finally, a real-time experiment involving continuous metric monitoring allowed personalized dynamic optimization of the current amplitude and stimulation site (frontal or parietal). The findings reveal statistically significant improvements in mean accuracy (94.04 vs. 90.82%) and reaction times (262.93 vs. 302.03 ms) with the adaptive tDCS compared to a non-stimulation condition. Average reaction times were statistically shorter during adaptive stimulation compared to a fixed current amplitude condition (262.93 vs. 283.56 ms), while mean accuracy stayed similar (94.04 vs. 93.36%, improvement not statistically significant). Despite the limited number of subjects, this work points out the promising potential of adaptive tDCS as a tailored treatment for enhancing sustained attention. Full article
(This article belongs to the Special Issue Adaptive Neurostimulation: Innovative Strategies for Stimulation)
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