SlideShare a Scribd company logo
1 of 15
O‘ZBEKISTON RESPUBLIKASI RAQAMLI TEXNOLOGIYALAR VAZIRLIGI
MUHAMMADAL-XORAZMIYNOMIDAGI TOSHKENTAXBOROT
TEXNOLOGIYALARI UNIVERSITETI QARSHI FILIALI
BITIRUV MALAKAVIY ISHI
MAVZU: TIBBIY SIGNALLARNI TASNIFLASH ASOSIDA MA’LUM
KASALLIKLARGA TASHXIS QO’YISH USULLARI VA ALGORITMLARI
Talaba: Abduraxmonova N
Raxbar : PhD., Zohirov Q
Mavzuning dolzarbligi.
◦ Hozirgi kunda zamonaviy tibbiyot amaliyotida qo’llaniladigan elektrotibbiyot apparatlarining texnik
vositalar umumiy tizimidagi o’rnini baholash uchun aynan shu apparatlarning qanday texnik
imkoniyatlarga va bemor organizmi uchun foydali tomonlari aks ettirish yoki turli xil kasalliklarni
diagnostika qilishda foydalaniladi, shuningdek kasalliklarning avj olish davrida yoki remissiya davrida
bu apparatlarning ma’lumotlari qay darajada o’zgarishini bilishimiz zarur.
◦ Qabul qiluvchi diagnostik qurilmalar organizmdagi turli jarayonlar – a’zo va to’qimalarda hosil
bo’layotgan biopotensiallar, yurak tonlari, tana harorati va boshqalar haqida ma’lumot beradi. Qabul
qiluvchi diagnostik qurilmalar ham barcha boshqa o’lchov moslamalari kabi tekshiriluvchi jarayonga
minimal ta’sir ko’rsatib, ma’lumotni juda kam o’zgarish bilan yetkazib berishi kerak.
Ishdan maqsad:
1. Inson tanasidagi biosignallarni tabiati va xususiyatlarini o’rganish;
2. Biosignallarni qayd qiluvchi apparat vositalarni ishlash prinsplarini tahlil
qilish;
3. Biosignallarni maxsus algoritmlar asosida tasniflash (klassifikatsiya qilish)
jarayonini amalga oshirish
Zamonaviy BITalino qurilmasining umumiy tavsifi
BITalino qurilmasining tuzilmasi quyidagilardan iborat (2-rasm):
1. BITalino board
2. Quvvat batarekasi (LiPo battery, LP553436-3.7V 700mAh)
3. Bluetooth 3.0
4. Sensorlar (3-5 dona)
5. USB kabel
Ushbu qurilma sensorlar bilan jihozlangan o’ta sezgir BITalino qurilmasi orqali inson tanasidagi vujudga
keladigan biosignal (biotok) larni qayd qilib boradi. Buning uchun albatta sensorlarni inson tanasiga qo’yish
shart emas. Ma’lum bir noqulayliklarni oldini olish maqsadida ushbu qurilma Bluetooth 3.0 texnologiyasi
bilan jihozlangan bo’lib, xech qanday qo’shimcha ulanishlarsiz xam o’ta sezgir qurilma orqali masofadan
xam natijalarni olish mumkin bo’ladi. Insonda 8 tadan ko’p turdagi biosignallar bo’lishi tibbiyotdan bizga
ma’lum. Demak biz o’zimizga kerak bo’ladigan biosignal turini tanlab olish imkoniyatidan xam
foydalanishimiz xam mumkin.(3-rasm)
Barcha yig’ilgan ma’lumotlarni hisobot ko’rinishida saqlab uni istalgan vaqtda ko’rish imkoniyati mavjud.
Bunda .h5 va .txt fayl ko’rinishida saqlanadi.
BIOSIGNALLARNI QAYTA ISHLASH USULLARI VAALGORITMI
Bizga ma’lumki biosignal yoki ixtiyoriy signallarning tarkibida shovqinlar (buzilishlar) bo’ladi. Demak,
sensorlar juda kichik bo’lgan shovqinni xam sezadigan bo’lishi kerak. Biz o’rganayotgan biosignallarning
amplituda ko’rsatkichlari juda kichik bo’lganligini uchun turli-xil shovqinlarga aralashib ketishga moyilligi kata
bo’ladi. Bunday shovqinlar sensorlarga tushadigan yorig’lik nuridan yoki tanadagi boshqa organlarning
tarqatayotgan signallaridan xosil bo’lishi mumkin. Inson tanasidagi signal tabiiy xolatda analog signal
hisoblanadi. Uni vizuallashtirish yoki ishlov berish uchun raqamli signal ko’rinishiga keltirishimiz kerak bo’ladi.
Biosignallarni qabul qilish va raqamli ko’rinishga keltirish bosqichlari rasmda keltirilgan.
EMG signal belgilarini tasniflash usul va algoritmini ishlab chiqish
Biosignallarni qayta ishlash bosqichi signalni qabul qilish va uzatish bosqichlarining o’rtasida
joylashgan muhim bosqicha sanaladi.
Ba'zi hollarda, qayta ishlash usullarini qo'llashdan oldin, ma'lumotlarni tahlil qilish, mos keladigan
ma'lumotni tayyorlash, dastlabki ishlov berish bosqichidan o'tishi kerak
Tasniflashni boshqa usullarini ko‘rib chiqamiz. Bular SVM, perseptron va tasodifiy daraxt usuli. Ushbu usullarning
xar biri uchun signalning belgilari ishlatiladi [7,8]. Foydalanilgan algoritmlar asosida quyidagi natijalarga erishildi:
 Perseptron tarmogida o‘qtishda jami sakkizta xatolik bo‘ldi (perseptronning parametrlari: uchta yashirin
qatlamdan birinchisida 10 ta neyron qatlami, ikkinchisida 15 ta va uchinchisida 5 ta neyron qatlami mavjud).
 SVM algoritmida esa bir xatolik topildi.
 Daraxt algoritmidagi o‘qitishda bir xatolik aniqlandi.
Testlash natijalari xaqidagi ma’lumotlar 2-jadvalda keltirilgan.
XULOSA
◦ Bitiruv ishida kо‘zlangan maqsad quyidagilar:
1.Biosignallarni turlarini tahlil qilish, elektromiografiya signalining xususiyatlarinin o’rganish.
2.Inson tanasidan biosignallarni yozib oladigan zamonaviy qurilmalarni o’rganish, ularning arxitekturasi va
ishlash prinspini aniqlash;
3.EMG signallari asosida qo’l xarakatlarini klasisfikatsiya qilishni amalga oshirish;
E’tiboringiz uchun raxmat!!!

More Related Content

Featured

Social Media Marketing Trends 2024 // The Global Indie Insights
Social Media Marketing Trends 2024 // The Global Indie InsightsSocial Media Marketing Trends 2024 // The Global Indie Insights
Social Media Marketing Trends 2024 // The Global Indie Insights
Kurio // The Social Media Age(ncy)
 
Good Stuff Happens in 1:1 Meetings: Why you need them and how to do them well
Good Stuff Happens in 1:1 Meetings: Why you need them and how to do them wellGood Stuff Happens in 1:1 Meetings: Why you need them and how to do them well
Good Stuff Happens in 1:1 Meetings: Why you need them and how to do them well
Saba Software
 

Featured (20)

Content Methodology: A Best Practices Report (Webinar)
Content Methodology: A Best Practices Report (Webinar)Content Methodology: A Best Practices Report (Webinar)
Content Methodology: A Best Practices Report (Webinar)
 
How to Prepare For a Successful Job Search for 2024
How to Prepare For a Successful Job Search for 2024How to Prepare For a Successful Job Search for 2024
How to Prepare For a Successful Job Search for 2024
 
Social Media Marketing Trends 2024 // The Global Indie Insights
Social Media Marketing Trends 2024 // The Global Indie InsightsSocial Media Marketing Trends 2024 // The Global Indie Insights
Social Media Marketing Trends 2024 // The Global Indie Insights
 
Trends In Paid Search: Navigating The Digital Landscape In 2024
Trends In Paid Search: Navigating The Digital Landscape In 2024Trends In Paid Search: Navigating The Digital Landscape In 2024
Trends In Paid Search: Navigating The Digital Landscape In 2024
 
5 Public speaking tips from TED - Visualized summary
5 Public speaking tips from TED - Visualized summary5 Public speaking tips from TED - Visualized summary
5 Public speaking tips from TED - Visualized summary
 
ChatGPT and the Future of Work - Clark Boyd
ChatGPT and the Future of Work - Clark Boyd ChatGPT and the Future of Work - Clark Boyd
ChatGPT and the Future of Work - Clark Boyd
 
Getting into the tech field. what next
Getting into the tech field. what next Getting into the tech field. what next
Getting into the tech field. what next
 
Google's Just Not That Into You: Understanding Core Updates & Search Intent
Google's Just Not That Into You: Understanding Core Updates & Search IntentGoogle's Just Not That Into You: Understanding Core Updates & Search Intent
Google's Just Not That Into You: Understanding Core Updates & Search Intent
 
How to have difficult conversations
How to have difficult conversations How to have difficult conversations
How to have difficult conversations
 
Introduction to Data Science
Introduction to Data ScienceIntroduction to Data Science
Introduction to Data Science
 
Time Management & Productivity - Best Practices
Time Management & Productivity -  Best PracticesTime Management & Productivity -  Best Practices
Time Management & Productivity - Best Practices
 
The six step guide to practical project management
The six step guide to practical project managementThe six step guide to practical project management
The six step guide to practical project management
 
Beginners Guide to TikTok for Search - Rachel Pearson - We are Tilt __ Bright...
Beginners Guide to TikTok for Search - Rachel Pearson - We are Tilt __ Bright...Beginners Guide to TikTok for Search - Rachel Pearson - We are Tilt __ Bright...
Beginners Guide to TikTok for Search - Rachel Pearson - We are Tilt __ Bright...
 
Unlocking the Power of ChatGPT and AI in Testing - A Real-World Look, present...
Unlocking the Power of ChatGPT and AI in Testing - A Real-World Look, present...Unlocking the Power of ChatGPT and AI in Testing - A Real-World Look, present...
Unlocking the Power of ChatGPT and AI in Testing - A Real-World Look, present...
 
12 Ways to Increase Your Influence at Work
12 Ways to Increase Your Influence at Work12 Ways to Increase Your Influence at Work
12 Ways to Increase Your Influence at Work
 
ChatGPT webinar slides
ChatGPT webinar slidesChatGPT webinar slides
ChatGPT webinar slides
 
More than Just Lines on a Map: Best Practices for U.S Bike Routes
More than Just Lines on a Map: Best Practices for U.S Bike RoutesMore than Just Lines on a Map: Best Practices for U.S Bike Routes
More than Just Lines on a Map: Best Practices for U.S Bike Routes
 
Ride the Storm: Navigating Through Unstable Periods / Katerina Rudko (Belka G...
Ride the Storm: Navigating Through Unstable Periods / Katerina Rudko (Belka G...Ride the Storm: Navigating Through Unstable Periods / Katerina Rudko (Belka G...
Ride the Storm: Navigating Through Unstable Periods / Katerina Rudko (Belka G...
 
Barbie - Brand Strategy Presentation
Barbie - Brand Strategy PresentationBarbie - Brand Strategy Presentation
Barbie - Brand Strategy Presentation
 
Good Stuff Happens in 1:1 Meetings: Why you need them and how to do them well
Good Stuff Happens in 1:1 Meetings: Why you need them and how to do them wellGood Stuff Happens in 1:1 Meetings: Why you need them and how to do them well
Good Stuff Happens in 1:1 Meetings: Why you need them and how to do them well
 

Taqdimot.ppt

  • 1. O‘ZBEKISTON RESPUBLIKASI RAQAMLI TEXNOLOGIYALAR VAZIRLIGI MUHAMMADAL-XORAZMIYNOMIDAGI TOSHKENTAXBOROT TEXNOLOGIYALARI UNIVERSITETI QARSHI FILIALI BITIRUV MALAKAVIY ISHI MAVZU: TIBBIY SIGNALLARNI TASNIFLASH ASOSIDA MA’LUM KASALLIKLARGA TASHXIS QO’YISH USULLARI VA ALGORITMLARI Talaba: Abduraxmonova N Raxbar : PhD., Zohirov Q
  • 2. Mavzuning dolzarbligi. ◦ Hozirgi kunda zamonaviy tibbiyot amaliyotida qo’llaniladigan elektrotibbiyot apparatlarining texnik vositalar umumiy tizimidagi o’rnini baholash uchun aynan shu apparatlarning qanday texnik imkoniyatlarga va bemor organizmi uchun foydali tomonlari aks ettirish yoki turli xil kasalliklarni diagnostika qilishda foydalaniladi, shuningdek kasalliklarning avj olish davrida yoki remissiya davrida bu apparatlarning ma’lumotlari qay darajada o’zgarishini bilishimiz zarur. ◦ Qabul qiluvchi diagnostik qurilmalar organizmdagi turli jarayonlar – a’zo va to’qimalarda hosil bo’layotgan biopotensiallar, yurak tonlari, tana harorati va boshqalar haqida ma’lumot beradi. Qabul qiluvchi diagnostik qurilmalar ham barcha boshqa o’lchov moslamalari kabi tekshiriluvchi jarayonga minimal ta’sir ko’rsatib, ma’lumotni juda kam o’zgarish bilan yetkazib berishi kerak.
  • 3. Ishdan maqsad: 1. Inson tanasidagi biosignallarni tabiati va xususiyatlarini o’rganish; 2. Biosignallarni qayd qiluvchi apparat vositalarni ishlash prinsplarini tahlil qilish; 3. Biosignallarni maxsus algoritmlar asosida tasniflash (klassifikatsiya qilish) jarayonini amalga oshirish
  • 5. BITalino qurilmasining tuzilmasi quyidagilardan iborat (2-rasm): 1. BITalino board 2. Quvvat batarekasi (LiPo battery, LP553436-3.7V 700mAh) 3. Bluetooth 3.0 4. Sensorlar (3-5 dona) 5. USB kabel
  • 6. Ushbu qurilma sensorlar bilan jihozlangan o’ta sezgir BITalino qurilmasi orqali inson tanasidagi vujudga keladigan biosignal (biotok) larni qayd qilib boradi. Buning uchun albatta sensorlarni inson tanasiga qo’yish shart emas. Ma’lum bir noqulayliklarni oldini olish maqsadida ushbu qurilma Bluetooth 3.0 texnologiyasi bilan jihozlangan bo’lib, xech qanday qo’shimcha ulanishlarsiz xam o’ta sezgir qurilma orqali masofadan xam natijalarni olish mumkin bo’ladi. Insonda 8 tadan ko’p turdagi biosignallar bo’lishi tibbiyotdan bizga ma’lum. Demak biz o’zimizga kerak bo’ladigan biosignal turini tanlab olish imkoniyatidan xam foydalanishimiz xam mumkin.(3-rasm)
  • 7. Barcha yig’ilgan ma’lumotlarni hisobot ko’rinishida saqlab uni istalgan vaqtda ko’rish imkoniyati mavjud. Bunda .h5 va .txt fayl ko’rinishida saqlanadi.
  • 8. BIOSIGNALLARNI QAYTA ISHLASH USULLARI VAALGORITMI Bizga ma’lumki biosignal yoki ixtiyoriy signallarning tarkibida shovqinlar (buzilishlar) bo’ladi. Demak, sensorlar juda kichik bo’lgan shovqinni xam sezadigan bo’lishi kerak. Biz o’rganayotgan biosignallarning amplituda ko’rsatkichlari juda kichik bo’lganligini uchun turli-xil shovqinlarga aralashib ketishga moyilligi kata bo’ladi. Bunday shovqinlar sensorlarga tushadigan yorig’lik nuridan yoki tanadagi boshqa organlarning tarqatayotgan signallaridan xosil bo’lishi mumkin. Inson tanasidagi signal tabiiy xolatda analog signal hisoblanadi. Uni vizuallashtirish yoki ishlov berish uchun raqamli signal ko’rinishiga keltirishimiz kerak bo’ladi. Biosignallarni qabul qilish va raqamli ko’rinishga keltirish bosqichlari rasmda keltirilgan.
  • 9.
  • 10. EMG signal belgilarini tasniflash usul va algoritmini ishlab chiqish Biosignallarni qayta ishlash bosqichi signalni qabul qilish va uzatish bosqichlarining o’rtasida joylashgan muhim bosqicha sanaladi. Ba'zi hollarda, qayta ishlash usullarini qo'llashdan oldin, ma'lumotlarni tahlil qilish, mos keladigan ma'lumotni tayyorlash, dastlabki ishlov berish bosqichidan o'tishi kerak
  • 11.
  • 12.
  • 13. Tasniflashni boshqa usullarini ko‘rib chiqamiz. Bular SVM, perseptron va tasodifiy daraxt usuli. Ushbu usullarning xar biri uchun signalning belgilari ishlatiladi [7,8]. Foydalanilgan algoritmlar asosida quyidagi natijalarga erishildi:  Perseptron tarmogida o‘qtishda jami sakkizta xatolik bo‘ldi (perseptronning parametrlari: uchta yashirin qatlamdan birinchisida 10 ta neyron qatlami, ikkinchisida 15 ta va uchinchisida 5 ta neyron qatlami mavjud).  SVM algoritmida esa bir xatolik topildi.  Daraxt algoritmidagi o‘qitishda bir xatolik aniqlandi. Testlash natijalari xaqidagi ma’lumotlar 2-jadvalda keltirilgan.
  • 14. XULOSA ◦ Bitiruv ishida kо‘zlangan maqsad quyidagilar: 1.Biosignallarni turlarini tahlil qilish, elektromiografiya signalining xususiyatlarinin o’rganish. 2.Inson tanasidan biosignallarni yozib oladigan zamonaviy qurilmalarni o’rganish, ularning arxitekturasi va ishlash prinspini aniqlash; 3.EMG signallari asosida qo’l xarakatlarini klasisfikatsiya qilishni amalga oshirish;