Ushbu maqolada boks sport turiga ixtisoslashgan sportchilarning mushak faolligi va toliqish darajasini elektromiografik (EMG) signallar asosida avtomatik aniqlashning intellektual usuli taklif etilgan. Tadqiqotning asosiy maqsadi EMG signallaridan olingan vaqt, chastota va nochiziqli dinamika xusuiyatlarining optimal kombinatsiyasini aniqlash orqali tasniflash aniqligini oshirishdan iborat. Eksperimental tadqiqotlarda turli malaka darajasidagi 31 nafar sportchi ishtirok etdi va ulardan olingan signallar asosida 7 xil tarkibdagi xususiyatlar majmuasi (Feature Sets) shakllantirildi. Ma’lumotlarni qayta ishlash uchun modifikatsiyalangan faollashtirish funksiyasiga ega bo‘lgan Ko‘p qatlamli perceptron (MLP) neyron tarmog‘i ishlab chiqildi. Tahlil natijalari shuni ko‘rsatdiki, vaqt (RMS, MAV), chastota (MDF, MNF) va fiziologik (BMI, HR) parametrlarni o‘z ichiga olgan integratsiyalashgan XM7 xususiyatlar majmuasi mushak holatini baholashda eng yuqori samaradorlikni namoyon etdi. Statistik tahlilda spektral ko‘rsatkichlarning diskriminativ quvvati yuqori ekanligi () va taklif etilgan modelning F1-score ko‘rsatkichi 0.96 ga tengligi aniqlandi. Ushbu yondashuv sportchilarning mashg‘ulot jarayonini monitoring qilish va jarohatlarni oldini olish tizimlarida qo‘llash uchun tavsiya etiladi.
| Mualliflar | Shokhrukhmirzo Kholdorov |
|---|---|
| Jurnal | ТАТУ хабарлари |
| Nashr sanasi | 2026-03-20 |
| Til | uz |
| DOI | 10.5281/zenodo.21451277 |
DOI: 10.5281/zenodo.21451277 · Maqolaning asl sahifasi
Ushbu maqolada boks sport turiga ixtisoslashgan sportchilarning mushak faolligi va toliqish darajasini elektromiografik (EMG) signallar asosida avtomatik aniqlashning intellektual usuli taklif etilgan. Tadqiqotning…
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