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All Journal Jurnal Penelitian Fisika dan Aplikasinya (JPFA) IPTEK Journal of Science JURNAL PENGABDIAN KEPADA MASYARAKAT Gravity : Jurnal Ilmiah Penelitian dan Pembelajaran Fisika Jurnal Fisika FLUX Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer INDONESIAN JOURNAL OF APPLIED PHYSICS MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Basicedu Jurnal Ilmu Fisika Abdimas Umtas : Jurnal Pengabdian kepada Masyarakat PROJECT (Professional Journal of English Education) Jurnal Computer Science and Information Technology (CoSciTech) International Journal of Community Service Inovasi Fisika Indonesia (IFI) YASIN: Jurnal Pendidikan dan Sosial Budaya MASALIQ: Jurnal Pendidikan dan Sains Journal of Health Management, Administration and Public Health Policies
Uswatun Chasanah
Universitas Muhammadiyah Lamongan
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Computer Science & IT Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Physics Public Health Social Sciences Other

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Design and Construction of a Bipolar Disorder Detection Device Based on Anomalies in the Frequency of Conversational Sound Waves Using the Max9814 Sensor Badiyah, Rohmatul; Chasanah, Uswatun; Makrufah, Asmaul Lutfi; Widodo, Aris; Annas, Muhamad Azwar
Gravity : Jurnal Ilmiah Penelitian dan Pembelajaran Fisika Vol 11, No 2 (2025)
Publisher : Universitas Sultan Ageng Tirtayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62870/gravity.v11i2.34826

Abstract

Bipolar disorder is a mental health condition that causes extremely dramatic mood swings, from very high (mania) to very low (depression). Physically, mood changes can be identified from variations in sound frequency. However, early detection of individuals suspected of having bipolar disorder remains a challenge due to the limited availability of tools and healthcare facilities. This research aims to design a bipolar disorder detection tool based on anomalies in the frequency of conversational sound waves using the MAX9814 sensor as a preventive measure for bipolar disorder, with the novelty of the research being its connection to IoT, enabling real-time monitoring of bipolar patients' emotional conditions. The system design uses Arduino Nano as the data processor, and ESP8266 module for IoT connectivity, with testing method conducted on ten respondents with five variations of emotion combinations. The testing method was performed on  10 people (5 men and 5 women) aged 20–40 years, who recited sentences combining variations of depression and mania. The research results show that the device is able to detect changes in voice frequency with an average error of 5% and an accuracy of 95%. The range of sound frequencies indicative of bipolar disorder is 190–355 Hz, with the following patterns: anger < 320 Hz, happiness < 300 Hz, sadness and fear > 240 Hz, especially if negative sounds are the highest. In individuals with bipolar disorder, voice frequencies can change suddenly by more than ±50 Hz within a single sentence. These findings prove that the developed tool has high sensitivity in detecting emotional changes based on voice frequency and can be used as a supporting instrument in the early detection of bipolar disorder efficiently and sustainably.
Co-Authors AFIFI MUTIARANI Aini, Latifatun Nur Annas, Muhamad Azwar Aris Widodo Aris Widodo Aris Widodo Asmaul Lutfi Marufah Ayu Sugiarti, Vanis Aisyatul Badiyah, Rohmatul Badiyah, Rohmatul Eko Handoyo Fais Wahidatul Arifatin Garist Sekar Tanjung Henny Dwi Bhakti Humairah Humairah Irwan Setyowidodo, Bagus Jaya Santosa Lilik Wahyuni P Madlazim Madlazim Madlazim, M Mafruudloh, Naajihah Makrufah, Asmaul Lutfi Mala Rosa Aprillya Masria Musfiana Mufti Ari Bianto Muhamad Azwar Annas Muktamar Cholifah Aisiyah Nesya Nuur Rahmawati Nia Shohaya, Jihan Ningrum, Izza Eka Sandi, Aris Siti Diah Ayu Febriani Tjipto Prastowo