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22 pages, 8251 KiB

Open AccessArticle

Advances in Non-Invasive Neuromodulation: Designing Closed-Loop Devices for Respiratory-Controlled Transcutaneous Vagus Nerve Stimulation

by Gabriella Maria de Faria, Eugênia Gonzales Lopes, Eleonora Tobaldini, Nicola Montano, Tatiana Sousa Cunha, Karina Rabello Casali and Henrique Alves de Amorim

Healthcare 2024, 12(1), 31; https://doi.org/10.3390/healthcare12010031 - 22 Dec 2023

Cited by 2 | Viewed by 2017

Abstract

Studies suggest non-invasive transcutaneous auricular vagus nerve stimulation (taVNS) as a potential therapeutic option for various pathological conditions, such as epilepsy and depression. Exhalation-controlled taVNS, which synchronizes stimulation with internal body rhythms, holds promise for enhanced neuromodulation, but there is no closed-loop system [...] Read more.

Studies suggest non-invasive transcutaneous auricular vagus nerve stimulation (taVNS) as a potential therapeutic option for various pathological conditions, such as epilepsy and depression. Exhalation-controlled taVNS, which synchronizes stimulation with internal body rhythms, holds promise for enhanced neuromodulation, but there is no closed-loop system in the literature capable of performing such integration in real time. In this context, the objective was to develop real-time signal processing techniques and an integrated closed-loop device with sensors to acquire physiological data. After a conditioning stage, the signal is processed and delivers synchronized electrical stimulation during the patient’s expiratory phase. Additional modules were designed for processing, software-controlled selectors, remote and autonomous operation, improved analysis, and graphical visualization. The signal processing method effectively extracted respiratory cycles and successfully attenuated signal noise. Heart rate variability was assessed in real time, using linear statistical evaluation. The prototype feedback stimulator device was physically constructed. Respiratory peak detection achieved an accuracy of 90%, and the real-time processing resulted in a small delay of up to 150 ms in the detection of the expiratory phase. Thus, preliminary results show promising accuracy, indicating the need for additional tests to optimize real-time processing and the application of the prototype in clinical studies. Full article

(This article belongs to the Special Issue Innovations in Biomedical Signal Processing and Modeling for a Better Healthcare)

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22 pages, 1324 KiB

Open AccessArticle

An Intelligent System to Improve Diagnostic Support for Oral Squamous Cell Carcinoma

by Afonso U. Fonseca, Juliana P. Felix, Hedenir Pinheiro, Gabriel S. Vieira, Ýleris C. Mourão, Juliana C. G. Monteiro and Fabrizzio Soares

Healthcare 2023, 11(19), 2675; https://doi.org/10.3390/healthcare11192675 - 3 Oct 2023

Viewed by 1494

Abstract

Oral squamous cell carcinoma (OSCC) is one of the most-prevalent cancer types worldwide, and it poses a serious threat to public health due to its high mortality and morbidity rates. OSCC typically has a poor prognosis, significantly reducing the chances of patient survival. [...] Read more.

Oral squamous cell carcinoma (OSCC) is one of the most-prevalent cancer types worldwide, and it poses a serious threat to public health due to its high mortality and morbidity rates. OSCC typically has a poor prognosis, significantly reducing the chances of patient survival. Therefore, early detection is crucial to achieving a favorable prognosis by providing prompt treatment and increasing the chances of remission. Salivary biomarkers have been established in numerous studies to be a trustworthy and non-invasive alternative for early cancer detection. In this sense, we propose an intelligent system that utilizes feed-forward artificial neural networks to classify carcinoma with salivary biomarkers extracted from control and OSCC patient samples. We conducted experiments using various salivary biomarkers, ranging from 1 to 51, to train the model, and we achieved excellent results with precision, sensitivity, and specificity values of 98.53%, 96.30%, and 97.56%, respectively. Our system effectively classified the initial cases of OSCC with different amounts of biomarkers, aiding medical professionals in decision-making and providing a more-accurate diagnosis. This could contribute to a higher chance of treatment success and patient survival. Furthermore, the minimalist configuration of our model presents the potential for incorporation into resource-limited devices or environments. Full article

(This article belongs to the Special Issue Innovations in Biomedical Signal Processing and Modeling for a Better Healthcare)

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13 pages, 2773 KiB

Open AccessArticle

Influence of Binaural Beats Stimulation of Gamma Frequency over Memory Performance and EEG Spectral Density

by Ludymila Ribeiro Borges, Ana Paula Bittar Britto Arantes and Eduardo Lazaro Martins Naves

Healthcare 2023, 11(6), 801; https://doi.org/10.3390/healthcare11060801 - 9 Mar 2023

Cited by 3 | Viewed by 4658

Abstract

Similar to short-term memory, working memory cannot hold information for a long period of time. Studies have shown that binaural beats (BB) can stimulate the brain through sound, affecting working memory function. Although the literature is not conclusive regarding the effects of BB [...] Read more.

Similar to short-term memory, working memory cannot hold information for a long period of time. Studies have shown that binaural beats (BB) can stimulate the brain through sound, affecting working memory function. Although the literature is not conclusive regarding the effects of BB stimulation (stim) on memory, some studies have shown that gamma-BB stim (40 Hz) can increase attentional focusing and improve visual working memory. To better understand the relationship between BB stim and memory, we collected electroencephalographic data (EEG) from 30 subjects in 3 phases—a baseline, with gamma-BB stim, and control stim—in a rest state, with eyes closed, and while performing memory tasks. Both EEG data and memory task performance were analyzed. The results showed no significant changes in the memory task performance or the EEG data when comparing experimental and control conditions. We concluded that brain entrainment was not achieved with our parameters of gamma-BB stimulation when analyzing EEG power spectral density (PSD) and memory task performance. Hence, we suggest that other aspects of EEG data, such as connectivity and correlations with task performance, should also be analyzed for future studies. Full article

(This article belongs to the Special Issue Innovations in Biomedical Signal Processing and Modeling for a Better Healthcare)

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20 pages, 2655 KiB

Open AccessArticle

A Novel Physical Mobility Task to Assess Freezers in Parkinson’s Disease

by Lígia Reis Nóbrega, Eduardo Rocon, Adriano Alves Pereira and Adriano de Oliveira Andrade

Healthcare 2023, 11(3), 409; https://doi.org/10.3390/healthcare11030409 - 31 Jan 2023

Cited by 3 | Viewed by 1762

Abstract

Freezing of gait (FOG), one of the most disabling features of Parkinson’s disease (PD), is a brief episodic absence or marked reduction in stride progression despite the intention to walk. Progressively more people who experience FOG restrict their walking and reduce their level [...] Read more.

Freezing of gait (FOG), one of the most disabling features of Parkinson’s disease (PD), is a brief episodic absence or marked reduction in stride progression despite the intention to walk. Progressively more people who experience FOG restrict their walking and reduce their level of physical activity. The purpose of this study is to develop and validate a physical mobility task that induces freezing of gait in a controlled environment, employing known triggers of FOG episodes according to the literature. To validate the physical mobility tasks, we recruited 10 volunteers that suffered PD-associated freezing (60.6 ± 7.29 years-old) with new FOG-Q ranging from 12 to 26. The validation of the proposed method was carried out using inertial sensors and video recordings. All subjects were assessed during the OFF and ON medication states. The total number of FOG occurrences during data collection was 144. The proposed tasks were able to trigger 120 FOG episodes, while the TUG test caused 24. The Inertial Measurement Unit (IMU) with accelerometer and gyroscope could not only detect FOG episodes but also allowed us to visualize the three types of FOG: akinesia, festination and trembling in place. Full article

(This article belongs to the Special Issue Innovations in Biomedical Signal Processing and Modeling for a Better Healthcare)

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18 pages, 3278 KiB

Open AccessArticle

Identification and Characterization of Short-Term Motor Patterns in Rest Tremor of Individuals with Parkinson’s Disease

by Amanda Rabelo, João Paulo Folador, Ariana Moura Cabral, Viviane Lima, Ana Paula Arantes, Luciane Sande, Marcus Fraga Vieira, Rodrigo Maximiano Antunes de Almeida and Adriano de Oliveira Andrade

Healthcare 2022, 10(12), 2536; https://doi.org/10.3390/healthcare10122536 - 14 Dec 2022

Cited by 4 | Viewed by 1880

Abstract

(1) Background: The dynamics of hand tremors involve nonrandom and short-term motor patterns (STMPs). This study aimed to (i) identify STMPs in Parkinson’s disease (PD) and physiological resting tremor and (ii) characterize STMPs by amplitude, persistence, and regularity. (2) Methods: This study included [...] Read more.

(1) Background: The dynamics of hand tremors involve nonrandom and short-term motor patterns (STMPs). This study aimed to (i) identify STMPs in Parkinson’s disease (PD) and physiological resting tremor and (ii) characterize STMPs by amplitude, persistence, and regularity. (2) Methods: This study included healthy (N = 12, 60.1 ± 5.9 years old) and PD (N = 14, 65 ± 11.54 years old) participants. The signals were collected using a triaxial gyroscope on the dorsal side of the hand during a resting condition. Data were preprocessed and seven features were extracted from each 1 s window with 50% overlap. The STMPs were identified using the clustering technique k-means applied to the data in the two-dimensional space given by t-Distributed Stochastic Neighbor Embedding (t-SNE). The frequency, transition probability, and duration of the STMPs for each group were assessed. All STMP features were averaged across groups. (3) Results: Three STMPs were identified in tremor signals (p < 0.05). STMP 1 was prevalent in the healthy control (HC) subjects, STMP 2 in both groups, and STMP3 in PD. Only the coefficient of variation and complexity differed significantly between groups. (4) Conclusion: These results can help professionals characterize and evaluate tremor severity and treatment efficacy. Full article

(This article belongs to the Special Issue Innovations in Biomedical Signal Processing and Modeling for a Better Healthcare)

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31 pages, 4562 KiB

Open AccessArticle

Multidimensional Assessment of Individuals with Parkinson’s Disease: Development and Structure Validation of a Self-Assessment Questionnaire

by Luanne Cardoso Mendes, Isabela Alves Marques, Camille Marques Alves, Marcus Fraga Vieira, Edgard Afonso Lamounier Júnior, Adriano Alves Pereira, Eduardo Lázaro Martins Naves, Fábio Henrique Monteiro Oliveira, Guy Bourhis, Pierre Pino, Yann Morère and Adriano de Oliveira Andrade

Healthcare 2022, 10(10), 1823; https://doi.org/10.3390/healthcare10101823 - 21 Sep 2022

Cited by 1 | Viewed by 2038

Abstract

(1) Background: Several instruments are used to assess individuals with Parkinson’s disease (PD). However, most instruments necessitate the physical presence of a clinician for evaluation, were not designed for PD, nor validated for remote application. (2) Objectives: To develop and validate a self-assessment [...] Read more.

(1) Background: Several instruments are used to assess individuals with Parkinson’s disease (PD). However, most instruments necessitate the physical presence of a clinician for evaluation, were not designed for PD, nor validated for remote application. (2) Objectives: To develop and validate a self-assessment questionnaire that can be used remotely, and to assess the respondents’ health condition. (3) Methods: A questionnaire, so-called Multidimensional Assessment Questionnaire for Individuals with PD (MAQPD), was developed, administered remotely, and completed by 302 people with PD. MAQPD was validated using factor analysis (FA). The participants’ level of impairment was estimated using factor loadings. The scale’s accuracy was assessed estimating floor and ceiling effects and Cronbach’s alpha. (4) Results: FA suggested classifying the questions into daily activities, cognition, and pain. The respondents did not have extremely severe impairment (most scores ranged from 100 to 180 points), and the factors with the lowest scores were cognition and pain. The instrument had no significant floor or ceiling effects (rates less than 15%), and the Cronbach’s alpha value was larger than 0.90. (5) Conclusion: MAQPD is the only remote self-administered tool found in the literature capable of providing a detailed assessment of the general health status of individuals with PD. Full article

(This article belongs to the Special Issue Innovations in Biomedical Signal Processing and Modeling for a Better Healthcare)

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19 pages, 4765 KiB

Open AccessArticle

Wrist Movement Variability Assessment in Individuals with Parkinson’s Disease

by Lígia Reis Nóbrega, Ariana Moura Cabral, Fábio Henrique Monteiro Oliveira, Adriano de Oliveira Andrade, Sridhar Krishnan and Adriano Alves Pereira

Healthcare 2022, 10(9), 1656; https://doi.org/10.3390/healthcare10091656 - 30 Aug 2022

Cited by 3 | Viewed by 2348

Abstract

(1) Background: Parkinson’s disease (PD) is a neurodegenerative disorder represented by the progressive loss of dopamine-producing neurons, it decreases the individual’s motor functions and affects the execution of movements. There is a real need to include quantitative techniques and reliable methods to assess [...] Read more.

(1) Background: Parkinson’s disease (PD) is a neurodegenerative disorder represented by the progressive loss of dopamine-producing neurons, it decreases the individual’s motor functions and affects the execution of movements. There is a real need to include quantitative techniques and reliable methods to assess the evolution of PD. (2) Methods: This cross-sectional study assessed the variability of wrist RUD (radial and ulnar deviation) and FE (flexion and extension) movements measured by two pairs of capacitive sensors (PS25454 EPIC). The hypothesis was that PD patients have less variability in wrist movement execution than healthy individuals. The data was collected from 29 participants (age: 62.13 ± 9.7) with PD and 29 healthy individuals (60.70 ± 8). Subjects performed the experimental tasks at normal and fast speeds. Six features that captured the amplitude of the hand movements around two axes were estimated from the collected signals. (3) Results: The movement variability was greater for healthy individuals than for PD patients (p < 0.05). (4) Conclusion: The low variability seen in the PD group may indicate they execute wrist RUD and FE in a more restricted way. The variability analysis proposed here could be used as an indicator of patient progress in therapeutic programs and required changes in medication dosage. Full article

(This article belongs to the Special Issue Innovations in Biomedical Signal Processing and Modeling for a Better Healthcare)

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Review

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15 pages, 1252 KiB

Open AccessReview

Wrist Rigidity Evaluation in Parkinson’s Disease: A Scoping Review

by Camille Marques Alves, Andressa Rastrelo Rezende, Isabela Alves Marques, Luanne Cardoso Mendes, Angela Abreu Rosa de Sá, Marcus Fraga Vieira, Edgard Afonso Lamounier Júnior, Adriano Alves Pereira, Fábio Henrique Monteiro Oliveira, Luciane Pascucci Sande de Souza, Guy Bourhis, Pierre Pino, Adriano de Oliveira Andrade, Yann Morère and Eduardo Lázaro Martins Naves

Healthcare 2022, 10(11), 2178; https://doi.org/10.3390/healthcare10112178 - 31 Oct 2022

Cited by 4 | Viewed by 2306

Abstract

(1) Background: One of the main cardinal signs of Parkinson’s disease (PD) is rigidity, whose assessment is important for monitoring the patient’s recovery. The wrist is one of the joints most affected by this symptom, which has a great impact on activities of [...] Read more.

(1) Background: One of the main cardinal signs of Parkinson’s disease (PD) is rigidity, whose assessment is important for monitoring the patient’s recovery. The wrist is one of the joints most affected by this symptom, which has a great impact on activities of daily living and consequently on quality of life. The assessment of rigidity is traditionally made by clinical scales, which have limitations due to their subjectivity and low intra- and inter-examiner reliability. (2) Objectives: To compile the main methods used to assess wrist rigidity in PD and to study their validity and reliability, a scope review was conducted. (3) Methods: PubMed, IEEE/IET Electronic Library, Web of Science, Scopus, Cochrane, Bireme, Google Scholar and Science Direct databases were used. (4) Results: Twenty-eight studies were included. The studies presented several methods for quantitative assessment of rigidity using instruments such as force and inertial sensors. (5) Conclusions: Such methods present good correlation with clinical scales and are useful for detecting and monitoring rigidity. However, the development of a standard quantitative method for assessing rigidity in clinical practice remains a challenge. Full article

(This article belongs to the Special Issue Innovations in Biomedical Signal Processing and Modeling for a Better Healthcare)

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