المهارات neurokit2
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neurokit2

آمن ⚙️ الأوامر الخارجية🌐 الوصول إلى الشبكة

تحليل الإشارات الفسيولوجية الحيوية باستخدام NeuroKit2

متاح أيضًا من: K-Dense-AI

تتطلب معالجة الإشارات الفسيولوجية مثل ECG و EEG خوارزميات متخصصة للترشيح واكتشاف القمم واستخراج المعالم. توفر هذه المهارة وثائق شاملة وخطوط عمل لتحليل الإشارات العصبية والقلبية والأوعية الدموية باستخدام مكتبة Python الخاصة بـ NeuroKit2.

يدعم: Claude Codex Code(CC)
📊 71 كافٍ
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فعّل وابدأ الاستخدام

اختبرها

استخدام "neurokit2". معالجة تسجيل ECG لمدة 5 دقائق لتحليل شامل لـ HRV

النتيجة المتوقعة:

  • تم تنظيف ECG باستخدام مرشح Butterworth عالي المرور (0.5 Hz) + تصفية خط الطاقة
  • تم اكتشاف قمم R باستخدام طريقة NeuroKit (متغير Pan-Tompkins)
  • تم تطبيق تصحيح القمامات: تم اكتشاف 3 ضربات شاذة وتصحيحها
  • مجال وقت HRV: SDNN=45ms، RMSSD=32ms، pNN50=15%
  • مجال تردد HRV: VLF=1200ms²، LF=980ms²، HF=650ms²، نسبة LF/HF=1.51
  • غير خطي HRV: SD1=23ms، SD2=58ms، DFA_alpha1=0.85، SampleEn=1.42
  • تقييم الجودة: 98% من ضربات القلب اجتازت حد الجودة

استخدام "neurokit2". تحليل ECG وEDA والتنفس المتزامنة أثناء اختبار الإجهاد

النتيجة المتوقعة:

  • ECG: معدل ضربات القلب زاد من 72 إلى 98 BPM أثناء مرحلة الإجهاد
  • EDA: تم اكتشاف استجابات طورية عند سعة قمة 3.2 μS
  • التنفس: معدل التنفس زاد من 14 إلى 22 نفس/دقيقة
  • RSA (تسرع الجيوب الأنفية التنفسي) انخفض بنسبة 45% أثناء الإجهاد
  • نسبة HRV LF/HF زادت من 1.2 إلى 3.8 (تنشيط الودي)
  • مرحلة الاستعادة: عادت المعايير إلى خط الأساس خلال 4 دقائق

التدقيق الأمني

آمن
v5 • 1/17/2026

This skill is a pure documentation wrapper for the NeuroKit2 Python library containing only markdown reference files. The static scanner flagged 1149 false positives by misidentifying Python code examples in markdown code blocks as shell commands, scientific terminology (entropy, complexity, LF/HF bands) as cryptographic algorithms, and HRV metrics (C1d, C2d) as C2 malware indicators. No executable code, scripts, network calls, or file system operations exist in this skill. The previous audit correctly classified this as safe.

14
الملفات التي تم فحصها
6,439
الأسطر التي تم تحليلها
2
النتائج
5
إجمالي عمليات التدقيق

عوامل الخطر

⚙️ الأوامر الخارجية (1054)
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skill-report.json:6 SKILL.md:276 SKILL.md:348 SKILL.md:349 SKILL.md:350
تم تدقيقه بواسطة: claude عرض سجل التدقيق →

درجة الجودة

45
الهندسة المعمارية
100
قابلية الصيانة
87
المحتوى
21
المجتمع
100
الأمان
91
الامتثال للمواصفات

ماذا يمكنك بناءه

دراسات العواطف متعددة الأنماط

حلل معدل ضربات القلب والتوصيل الكهربائي الجلدي وEMG الوجهي أثناء المنبهات العاطفية لدراسة استجابات الجهاز العصبي اللاإرادي.

تحليل نشاط الدماغ EEG

احسب قوة نطاق التردد واستخرج تسلسلات الحالات الدقيقة وحلل ديناميكيا الدماغ أثناء المهام المعرفية.

تقييم HRV القلبي

احسب مقاييس شاملة لتغير معدل ضربات القلب لتقييم الوظيفة اللاإرادية في السكان السريريين.

جرّب هذه الموجهات

سير عمل ECG الأساسي 
ساعدني في معالجة إشارة ECG لتحليل تغير معدل ضربات القلب. لدي إشارة مأخوذة بـ 1000 Hz. أرني خط الأنابيب الكامل بما في ذلك التنظيف واكتشاف قمة R وحساب مقاييس HRV في مجالات الوقت والتردد وغير الخطية.
دمج الإشارات المتعددة 
لدي تسجيلات ECG وتنفس وEDA متزامنة. أرني كيفية معالجة جميع الإشارات معًا باستخدام دالة bio_process واستخراج الميزات المتكاملة مثل تسرع الجيوب الأنفية التنفسي.
تحليل مرتبط بالأحداث 
أحتاج إلى تحليل الاستجابات الفسيولوجية المتزامنة مع الأحداث المثيرة. أرني كيفية اكتشاف الأحداث وإنشاء حقب حولها واستخراج المعالم المتعلقة بالأحداث لإشارات ECG وEDA.
تحليل حالات EEG الدقيقة 
ساعدني في إجراء تحليل حالات EEG الدقيقة على بيانات الراحة. يتضمن المعالجة المسبقة وتحديد العدد الأمثل من الحالات والتجزئة وحساب ديناميكيات الانتقال.

أفضل الممارسات

  • استخدم معدلات أخذ عينات مناسبة: ECG/EEG ≥250 Hz، EDA ≥20 Hz، PPG ≥50 Hz
  • طبق تصحيح القمامات قبل اكتشاف القمم لتحسين الموثوقية
  • بلغ عن مدة التسجيل حيث تختلف المتطلبات الدنيا حسب نوع التحليل

تجنب

  • استخدام تسجيلات قصيرة (<60 ثانية) لتحليل HRV في مجال التردد
  • تخطي تقييم جودة الإشارة قبل حساب المقاييس
  • تجاهل_checks واقعية فسيولوجية على القمم المكتشفة

الأسئلة المتكررة

ما معدل أخذ العينات الذي أحتاجه لإشارات مختلفة؟
تتطلب ECG وEEG ≥250 Hz كحد أدنى (1000 Hz مستحسن). تحتاج EDA ≥20 Hz. تتطلب PPG ≥50 Hz.
ما المدة التي يجب أن تكون عليها التسجيلات لتحليل موثوق؟
معدل ضربات القلب الأساسي: ≥10 ثوانٍ. مجال وقت HRV: ≥60 ثانية. مجال تردد HRV: 2-5 دقائق. HRV غير الخطية: 5+ دقائق.
هل يمكنني استخدام NeuroKit2 مع بيانات من جهازي؟
نعم. قم باستيراد بياناتك كمصفوفات NumPy. تأكد من معدل أخذ عينات متسق عبر القنوات.
هل بياناتي الفسيولوجية آمنة مع هذه المهارة؟
تحتوي هذه المهارة على الوثائق فقط. تحدث المعالجة محليًا باستخدام مكتبة Python الخاصة بـ NeuroKit2 على جهازك.
لماذا يفشل اكتشاف القمم لدي؟
تحقق من جودة الإشارة أولاً. المشكلات الشائعة: قطبية ECG المقلوبة أو ضوضاء مفرطة أو تلامس ضعيف للأقطاب الكهربائية أو معدل أخذ عينات منخفض جدًا.
كيف يقارن هذا بـ Kubios أو برامج HRV الأخرى؟
توفر NeuroKit2 وظائف أساسية متشابهة مع ميزة أنها مفتوحة المصدر ومبنية على Python ومتكاملة مع سير عمل علم البيانات.

تفاصيل المطور

المؤلف

davila7

الترخيص

MIT

المستودع

https://github.com/davila7/claude-code-templates/tree/main/cli-tool/components/skills/scientific/neurokit2

مرجع

main

بنية الملفات

📁 references/

📄 bio_module.md

📄 complexity.md

📄 ecg_cardiac.md

📄 eda.md

📄 eeg.md

📄 emg.md

📄 eog.md

📄 epochs_events.md

📄 hrv.md

📄 ppg.md

📄 rsp.md

📄 signal_processing.md

📄 SKILL.md