24-h continuous non-invasive multiparameter home monitoring of vitals in patients with Rett syndrome by an innovative wearable technology: evidence of an overlooked chronic fatigue status DOI Creative Commons
Silvia Leoncini, Lidia Boasiako,

Sofia Di Lucia

et al.

Frontiers in Neurology, Journal Year: 2024, Volume and Issue: 15

Published: June 17, 2024

Background Sleep is disturbed in Rett syndrome (RTT), a rare and progressive neurodevelopmental disorder primarily affecting female patients (prevalence 7.1/100,000 patients) linked to pathogenic variations the X-linked methyl-CpG-binding protein 2 ( MECP2 ) gene. Autonomic nervous system dysfunction with predominance of sympathetic (SNS) over parasympathetic (PSNS) reported RTT, along exercise fatigue increased sudden death risk. The aim present study was test feasibility continuous 24 h non-invasive home monitoring biological vitals (biovitals) by an innovative wearable sensor device pediatric adolescent/adult RTT patients. Methods A total 10 (mean age 18.3 ± 9.4 years, range 4.7–35.5 years) typical were enrolled. Clinical severity assessed validated scales. Heart rate (HR), respiratory (RR), skin temperature (SkT) monitored YouCare Wearable Medical Device (Accyourate Group SpA, L’Aquila, Italy). average percentage maximum HR (HRmax%) calculated. variability (HRV) expressed consolidated time-domain frequency-domain parameters. HR/LF (low frequency) ratio, indicating SNS activation under dynamic exercise, Simultaneous measurement indoor air quality variables performed patients’ contributions surrounding water vapor partial pressure [P H2O (pt)] carbon dioxide CO2 indirectly estimated. Results Of 6,559.79 biovital recordings, 5051.03 (77%) valid for data interpretation. wake hours 9.0 1.1 14.9 h, respectively. HRmax % [median: 71.86% (interquartile 61.03–82%)] 3.75 3.19–5.05)] elevated, independent from wake–sleep cycle. majority HRV time- parameters significantly higher p ≤ 0.031). ratio associated phenotype severity, disease progression, clinical sleep disorder, subclinical hypoxia, electroencephalographic observations multifocal epileptic activity general background slowing. Conclusion Our findings indicate 24-h RTT. Moreover, first time, HRmax% identified as potential objective markers fatigue, illness progression.

Language: Английский

Balancing privacy and health integrity: A novel framework for ECG signal analysis in immersive environments DOI Creative Commons

Vithurabiman Senthuran,

Uthayasanker Thayasivam, Iynkaran Natgunanathan

et al.

Computers in Biology and Medicine, Journal Year: 2025, Volume and Issue: 192, P. 110234 - 110234

Published: May 1, 2025

Language: Английский

Citations

0
Artificial intelligence and the electrocardiogram: A modern renaissance DOI
Stefano Palermi, Marco Vecchiato, Fu Siong Ng

et al.

European Journal of Internal Medicine, Journal Year: 2025, Volume and Issue: unknown

Published: May 1, 2025

Language: Английский

Citations

0
Validation of a New and Straightforward Algorithm to Evaluate Signal Quality during ECG Monitoring with Wearable Devices Used in a Clinical Setting DOI Creative Commons
Luca Neri,

Ilaria Gallelli,

M. Dall’Olio

et al.

Bioengineering, Journal Year: 2024, Volume and Issue: 11(3), P. 222 - 222

Published: Feb. 26, 2024

Background: Wearable devices represent a new approach for monitoring key clinical parameters, such as ECG signals, research and health purposes. These could outcompete medical in terms of affordability use out-clinic settings, allowing remote monitoring. The major limitation, especially when compared to implantable devices, is the presence artifacts. Several authors reported relevant percentage recording time with poor/unusable traces ECG, potentially hampering these this purpose. For reason, it utmost importance develop simple inexpensive system enabling user wearable have immediate feedback on quality acquired signal, real-time correction. Methods: A algorithm that can work real verify signal (acceptable unacceptable) was validated. Based statistical blindly tested by comparison tracings previously classified two expert cardiologists. Results: classifications 7200 10s-signal samples 20 patients commercial monitor were compared. has an overall efficiency approximately 95%, sensitivity 94.7% specificity 95.3%. Conclusions: results demonstrate even be used classify coarseness, allow intervention subject or technician.

Language: Английский

Citations

3
Charting Tomorrow’s Healthcare: A Traditional Literature Review for an Artificial Intelligence-Driven Future DOI Open Access
Brody M Fogleman,

Matthew Goldman,

Alexander B Holland

et al.

Cureus, Journal Year: 2024, Volume and Issue: unknown

Published: April 11, 2024

Electronic health record (EHR) systems have developed over time in parallel with general advancements mainstream technology. As artificially intelligent (AI) rapidly impact multiple societal sectors, it has become apparent that medicine is not immune from the influences of this powerful Particularly appealing how AI may aid improving healthcare efficiency note-writing automation. This literature review explores current state EHR technologies healthcare, specifically focusing on possibilities for addressing challenges through automation dictation and processes integration. offers a broad understanding existing capabilities potential advancements, emphasizing innovations such as voice-to-text dictation, wearable devices, AI-assisted procedure note dictation. The primary objective to provide researchers valuable insights, enabling them generate new within landscape. By exploring benefits, challenges, future integration, encourages development innovative solutions, goal enhancing patient care delivery efficiency.

Language: Английский

Citations

3
24-h continuous non-invasive multiparameter home monitoring of vitals in patients with Rett syndrome by an innovative wearable technology: evidence of an overlooked chronic fatigue status DOI Creative Commons
Silvia Leoncini, Lidia Boasiako,

Sofia Di Lucia

et al.

Frontiers in Neurology, Journal Year: 2024, Volume and Issue: 15

Published: June 17, 2024

Background Sleep is disturbed in Rett syndrome (RTT), a rare and progressive neurodevelopmental disorder primarily affecting female patients (prevalence 7.1/100,000 patients) linked to pathogenic variations the X-linked methyl-CpG-binding protein 2 ( MECP2 ) gene. Autonomic nervous system dysfunction with predominance of sympathetic (SNS) over parasympathetic (PSNS) reported RTT, along exercise fatigue increased sudden death risk. The aim present study was test feasibility continuous 24 h non-invasive home monitoring biological vitals (biovitals) by an innovative wearable sensor device pediatric adolescent/adult RTT patients. Methods A total 10 (mean age 18.3 ± 9.4 years, range 4.7–35.5 years) typical were enrolled. Clinical severity assessed validated scales. Heart rate (HR), respiratory (RR), skin temperature (SkT) monitored YouCare Wearable Medical Device (Accyourate Group SpA, L’Aquila, Italy). average percentage maximum HR (HRmax%) calculated. variability (HRV) expressed consolidated time-domain frequency-domain parameters. HR/LF (low frequency) ratio, indicating SNS activation under dynamic exercise, Simultaneous measurement indoor air quality variables performed patients’ contributions surrounding water vapor partial pressure [P H2O (pt)] carbon dioxide CO2 indirectly estimated. Results Of 6,559.79 biovital recordings, 5051.03 (77%) valid for data interpretation. wake hours 9.0 1.1 14.9 h, respectively. HRmax % [median: 71.86% (interquartile 61.03–82%)] 3.75 3.19–5.05)] elevated, independent from wake–sleep cycle. majority HRV time- parameters significantly higher p ≤ 0.031). ratio associated phenotype severity, disease progression, clinical sleep disorder, subclinical hypoxia, electroencephalographic observations multifocal epileptic activity general background slowing. Conclusion Our findings indicate 24-h RTT. Moreover, first time, HRmax% identified as potential objective markers fatigue, illness progression.

Language: Английский

Citations

3