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All Journal MNJ (Malang Neurology Journal) Journal of Pain, Vertigo and Headache
Riandono, Dody
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Neuroscience

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HARNESSING CLIENT-SIDE AI: DEVELOPMENT AND VALIDATION OF A TENSORFLOW.JS APPLICATION FOR NON-INVASIVE SNORING DETECTION Afif, Zamroni; Rakhmatiar, Rodhiyan; Munir, Badrul; Ala Qoonita Najma Haq, Nabiila; Sabda Alam, Satria; Amrus Ernanda, Shelby; Ayu Irnanda, Miranthi; Riandono, Dody
MNJ (Malang Neurology Journal) Vol. 12 No. 1 (2026): January
Publisher : PERDOSSI (Perhimpunan Dokter Spesialis Saraf Indonesia Cabang Malang) - Indonesian Neurological Association Branch of Malang cooperated with Neurology Residency Program, Faculty of Medicine Brawijaya University, Malang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.mnj.2026.012.01.08

Abstract

Background: Obstructive sleep apnea (OSA) is a prevalent global health issue, yet current monitoring methods are often inaccessible or impractical for routine, at-home use. Objective: This study addresses the need for simple, non-invasive tools for sleep quality assessment. Methods: We developed and evaluated a novel, browser-based snoring detection application leveraging TensorFlow.js. A binary classification model was trained on a balanced dataset of snoring and background noise audio. A key feature of the application is its client-side architecture, where all audio processing and model inference occur locally on the user's device, ensuring real-time performance and preserving user privacy. The model's performance was validated on a holdout test set using standard classification metrics. Results: The model demonstrated robust performance, achieving an overall accuracy of 94.12%, a sensitivity of 95.00%, and a specificity of 93.22% in distinguishing snoring from ambient noise. The application successfully generated useful session statistics for users, including total snoring duration, frequency, and the percentage of snoring time during a monitoring session. Conclusion: This study validates the use of a browser-based AI system as a reliable, scalable, and privacy-preserving tool for sleep quality monitoring. While not a diagnostic instrument, the application serves as a highly accessible preliminary screening and awareness tool. This approach represents a significant step toward democratizing sleep health monitoring and empowering individuals to take an active role in managing their well-being.
CLINICAL PROFILE AND PRE-INTERVENTIONAL TREATMENT PATTERNS OF LOW BACK PAIN PATIENTS UNDERGOING PULSED RADIOFREQUENCY THERAPY: A RETROSPECTIVE STUDY Mardi Santoso, Widodo; Riandono, Dody
Journal of Pain, Headache and Vertigo Vol. 7 No. 2 (2026): September
Publisher : PERDOSNI (Perhimpunan Dokter Spesialis Neurologi Indonesia Cabang Malang) - Indonesian Neurological Association Branch of Malang cooperated with Neurology Residency Program, Faculty of Medicine Brawijaya University, Malang, Indonesia

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Abstract

Introduction: Chronic pain, including Low Back Pain (LBP), is one of the major public health problems that has a significant impact on the quality of life of patients and global socioeconomic costs. Pulsed Radiofrequency (PRF) therapy is an innovative modality used to manage chronic pain, including LBP, with minimal invasiveness and low risk of tissue damage. This study aims to describe the profile of LBP patients undergoing PRF therapy at Dr. Saiful Anwar Regional Hospital during the period from January to March 2024. Methods: This study uses a retrospective descriptive design by analyzing patient medical record data at Dr. Saiful Anwar Regional Hospital in East Java. The research population is all LBP patients who underwent PRF therapy from January to March 2024. A total of 30 patients were selected as research samples using purposive sampling techniques according to inclusion and exclusion criteria. Results: Demographic analysis showed that the majority of patients were female (70%), with an age range of 56–65 years (53%). Most patients took 3–4 types of pharmacotherapy (70%) before undergoing PRF, which lasted 4–6 months (37%). A total of 90% of patients underwent the first PRF procedure, while only 10% underwent a second PRF. Conclusion: PRF therapy is an effective modality in managing chronic pain in LBP patients, especially after long-term pharmacotherapy use. These findings provide important insights for developing PRF-based pain management strategies in the future. Further research is needed to evaluate the long-term effectiveness and clinical impact of this therapy in a wider population.
Co-Authors Afif, Zamroni Ala Qoonita Najma Haq, Nabiila Amrus Ernanda, Shelby Ayu Irnanda, Miranthi Badrul Munir, Badrul Mardi Santoso, Widodo Rakhmatiar, Rodhiyan Sabda Alam, Satria