## Resilient Mental Health Architecture

### 冗長性（Redundancy）
**Multiple Coping Strategies**：
- Primary: 運動・瞑想・睡眠最適化
- Secondary: 趣味・社会的活動・専門的サポート
- Tertiary: 環境変更・休暇・医療的介入

**Failover Mechanism**：
```python
class MentalHealthFailover:
    def handle_stress_event(self, stress_level):
        if stress_level < 30:
            return self.normal_operations()
        elif stress_level < 70:
            return self.activate_secondary_coping()
        elif stress_level < 90:
            return self.emergency_protocols()
        else:
            return self.crisis_management()
    
    def activate_secondary_coping(self):
        actions = [
            "reduce_non_essential_tasks",
            "activate_support_network", 
            "increase_recovery_time",
            "engage_stress_relief_activities"
        ]
        return self.execute_parallel(actions)

## Mental Load Balancing Strategies

### Temporal Load Balancing（時間的負荷分散）
**Daily Energy Budget Management**：
```yaml
energy_allocation:
  morning_peak: 
    allocation: 40%
    tasks: ["complex_problem_solving", "creative_work", "important_decisions"]
    recovery: "10min_break_every_90min"
  
  afternoon_steady:
    allocation: 35% 
    tasks: ["routine_implementation", "meetings", "code_reviews"]
    recovery: "15min_break_every_2hours"
  
  evening_decline:
    allocation: 25%
    tasks: ["administrative_work", "learning", "reflection"]
    recovery: "flexible_pacing"

stress_circuit_breaker:
  threshold: "cognitive_load > 85%"
  action: ["immediate_break", "task_postponement", "support_request"]
  recovery_time: "minimum_30min"

## Scaling Mental Health Resources

### External Resource Integration
**Support Network as Microservices**：

Personal Support Ecosystem:
┌─────────────────┐  ┌─────────────────┐  ┌─────────────────┐
│   Family/Friends │  │  Professional   │  │   Peer Network  │
│   Service        │  │   Service       │  │   Service       │
│                 │  │                 │  │                 │
│ ・Emotional      │  │ ・Counseling    │  │ ・技術的相談     │
│  Support        │  │ ・Medical Care  │  │ ・経験共有       │
│ ・日常的相談     │  │ ・専門的指導     │  │ ・同僚サポート   │
└─────────────────┘  └─────────────────┘  └─────────────────┘
         │                       │                       │
         └───────────────────────┼───────────────────────┘
                                 │
                  ┌─────────────────┐
                  │  Personal API   │
                  │   Gateway       │
                  │                 │
                  │ ・Request Router │
                  │ ・Load Balancer │
                  │ ・Health Checker │
                  └─────────────────┘

## Mental Health Metrics Collection

### Golden Signals for Personal Wellbeing

**Latency（応答性）**：
```python
class MentalLatencyMetrics:
    def measure_response_times(self):
        return {
            'decision_making_time': self.measure_decision_latency(),
            'problem_solving_speed': self.measure_cognitive_speed(),
            'emotional_recovery_time': self.measure_bounce_back(),
            'sleep_onset_latency': self.measure_sleep_quality()
        }
    
    def measure_decision_latency(self):
        # 通常の意思決定時間からの乖離を測定
        baseline = self.get_personal_baseline('decision_time')
        current = self.current_decision_time()
        
        if current > baseline * 1.5:
            return {'status': 'degraded', 'alert': True}
        else:
            return {'status': 'normal', 'alert': False}

## Emotion Tracking and Analysis

### 感情状態の構造化表現
**Multi-dimensional Emotion Model**：
```python
from dataclasses import dataclass
from enum import Enum
from typing import Dict, List
import datetime

class EmotionType(Enum):
    JOY = "joy"
    SADNESS = "sadness" 
    ANGER = "anger"
    FEAR = "fear"
    SURPRISE = "surprise"
    DISGUST = "disgust"
    CALM = "calm"
    EXCITED = "excited"

@dataclass
class EmotionReading:
    timestamp: datetime.datetime
    primary_emotion: EmotionType
    intensity: float  # 0.0 - 1.0
    confidence: float  # 0.0 - 1.0
    triggers: List[str]
    context: Dict[str, str]
    
    def to_metrics(self):
        return {
            'emotion_type': self.primary_emotion.value,
            'intensity_score': self.intensity,
            'trigger_count': len(self.triggers),
            'context_complexity': len(self.context)
        }

class EmotionAnalyzer:
    def analyze_patterns(self, readings: List[EmotionReading]):
        return {
            'dominant_emotions': self.get_emotion_distribution(readings),
            'intensity_trends': self.calculate_intensity_trends(readings),
            'trigger_patterns': self.identify_trigger_patterns(readings),
            'temporal_patterns': self.analyze_time_correlations(readings)
        }

## Stress Prediction System

### 機械学習によるストレス予測
**Feature Engineering for Stress Prediction**：
```python
class StressPredictionEngine:
    def extract_features(self, time_window_days=7):
        features = {}
        
        # 作業パターン特徴量
        features.update(self.extract_work_patterns())
        
        # 生理的特徴量  
        features.update(self.extract_physiological_signals())
        
        # 環境的特徴量
        features.update(self.extract_environmental_factors())
        
        # 社会的特徴量
        features.update(self.extract_social_interactions())
        
        return features
    
    def extract_work_patterns(self):
        return {
            'avg_daily_work_hours': self.calculate_work_hours(),
            'meeting_density': self.calculate_meeting_load(),
            'deadline_pressure': self.assess_upcoming_deadlines(),
            'task_complexity_score': self.evaluate_task_difficulty(),
            'context_switches_per_hour': self.count_task_switches(),
            'overtime_frequency': self.calculate_overtime_ratio()
        }
    
    def predict_stress_risk(self, features):
        # シンプルな予測モデル（実際は機械学習アルゴリズムを使用）
        risk_score = 0
        
        # 重み付けされた特徴量の組み合わせ
        if features['avg_daily_work_hours'] > 9:
            risk_score += 0.3
            
        if features['meeting_density'] > 0.4:  # 40%以上が会議
            risk_score += 0.2
            
        if features['deadline_pressure'] > 0.7:
            risk_score += 0.25
            
        if features['context_switches_per_hour'] > 8:
            risk_score += 0.15
            
        if features['sleep_quality_score'] < 0.6:
            risk_score += 0.1
            
        return min(risk_score, 1.0)  # 最大1.0に制限

## Self-Monitoring Dashboard Specification

### ダッシュボード・レイアウト設計
**Real-time Mental Health Metrics**：
```yaml
dashboard_layout:
  header:
    current_status:
      - overall_wellbeing_score: "0-100 score with color coding"
      - today_energy_level: "battery-style indicator"
      - stress_alert_status: "traffic light system"
    
  main_panels:
    stress_monitoring:
      components:
        - realtime_stress_level: "line chart, last 24h"
        - stress_triggers_today: "tag cloud with frequency"
        - prediction_next_3days: "forecast with confidence intervals"
      
    productivity_tracking:
      components:
        - focus_time_today: "progress bar vs target"
        - task_completion_rate: "percentage with trend"
        - quality_metrics: "error rate, rework frequency"
    
    recovery_status:
      components:
        - sleep_quality_trend: "7-day moving average"
        - exercise_consistency: "streak counter"
        - social_connection_index: "interaction quality score"

  sidebar:
    quick_actions:
      - stress_relief_suggestions: "context-aware recommendations"
      - emergency_contacts: "one-click access to support"
      - breathing_exercise_timer: "guided relaxation tools"
      
    insights:
      - pattern_alerts: "unusual patterns detected"
      - improvement_suggestions: "personalized recommendations"
      - milestone_celebrations: "positive reinforcement"

## Personal Agile Methodology

### スプリント設計（2週間サイクル）
**Sprint Planning for Personal Growth**：
```yaml
personal_sprint_framework:
  sprint_duration: "2週間"
  
  sprint_planning:
    duration: "1時間"
    activities:
      - previous_sprint_review: "成果と学習の振り返り"
      - goal_setting: "今回のスプリント目標設定"
      - task_breakdown: "具体的なタスクに分解"
      - capacity_planning: "リソース・時間の見積もり"
  
  daily_standups:
    duration: "10分（朝の振り返り）"
    questions:
      - "昨日達成したこと"
      - "今日やること"  
      - "ブロッカー・課題はあるか"
      - "エネルギーレベルはどうか"
  
  sprint_review:
    duration: "30分"
    activities:
      - achievement_demonstration: "成果の具体的確認"
      - metrics_analysis: "定量的な進捗評価"
      - stakeholder_feedback: "周囲からのフィードバック収集"
  
  sprint_retrospective:
    duration: "45分"
    focus_areas:
      - "何がうまくいったか"
      - "何を改善できるか"
      - "次のスプリントで試すこと"
      - "やめること・続けること・始めること"

## Mental Health Kanban Board

### カンバン・ボード設計
**Mental Wellness Task Flow**：

┌─────────────┐  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐
│   Backlog   │  │   To Do     │  │ In Progress │  │    Done     │
│             │  │             │  │             │  │             │
│ ストレス対策 │  │ 運動習慣化   │  │ 睡眠改善    │  │ 瞑想習慣    │
│ アイデア集  │  │            │  │ プログラム  │  │ 確立 ✓      │
│             │  │ コミュニケー │  │            │  │            │
│ ・読書習慣  │  │ ション改善  │  │ 週3回実施中 │  │ ストレス    │
│ ・SNS制限   │  │            │  │            │  │ 測定開始 ✓  │
│ ・趣味時間  │  │ 栄養バランス│  │ ヨガ・筋トレ │  │            │
│ ・環境整備  │  │ 見直し      │  │ 継続中      │  │ 環境音楽    │
│            │  │            │  │            │  │ 導入 ✓      │
└─────────────┘  └─────────────┘  └─────────────┘  └─────────────┘

WIP制限: To Do (3), In Progress (2) - 過負荷防止

## Kaizen for Mental Health

### 小さな改善の積み重ね
**1% Improvement Philosophy**：
```python
class PersonalKaizen:
    def __init__(self):
        self.improvement_areas = [
            "sleep_quality", "exercise_consistency", "stress_management",
            "social_connections", "learning_habits", "work_efficiency"
        ]
        self.current_baseline = self.establish_baseline()
    
    def daily_kaizen_cycle(self):
        """毎日1つの小さな改善を実装"""
        today_focus = self.select_improvement_area()
        small_change = self.design_minimal_improvement(today_focus)
        
        return {
            'area': today_focus,
            'change': small_change,
            'measurement': self.define_success_metric(small_change),
            'timeline': '24時間以内の実装・評価'
        }
    
    def design_minimal_improvement(self, area):
        improvements = {
            'sleep_quality': [
                "就寝30分前にスマホを別室に置く",
                "寝室温度を1度下げる", 
                "就寝時刻を10分早める"
            ],
            'stress_management': [
                "1日1回、5分間の深呼吸を追加",
                "ストレス感知時の対処法を1つ覚える",
                "感謝することを3つ書き出す"
            ],
            'work_efficiency': [
                "集中時間を25分→30分に延長",
                "会議前5分の準備時間を確保",
                "1日の終わりに明日の最重要タスクを1つ決める"
            ]
        }
        return random.choice(improvements.get(area, ["observe and document current state"]))

## Self-Experimentation Methodology

### 仮説駆動型の行動変容
**Hypothesis-Driven Self-Improvement**：
```yaml
experiment_template:
  hypothesis: 
    statement: "朝の瞑想習慣により、1日の集中力が向上する"
    measurable_outcome: "午前中の集中セッション継続時間"
    expected_improvement: "平均25分→35分（40%向上）"
  
  experimental_design:
    control_condition: "通常の朝ルーチン（運動→朝食→作業開始）"
    treatment_condition: "瞑想追加（運動→10分瞑想→朝食→作業開始）"
    duration: "各条件2週間ずつ"
    randomization: "週単位で条件をランダム切り替え"
  
  metrics:
    primary: 
      - focus_session_duration: "ポモドーロ・テクニック継続時間"
      - task_completion_rate: "午前中の計画タスク完了率"
    secondary:
      - subjective_wellbeing: "1-10スケールの主観的満足度"
      - stress_level: "午前中の平均ストレス値"
      - creative_output: "新しいアイデア・解決策の数"
  
  success_criteria:
    primary_threshold: "集中時間30%以上向上"
    secondary_threshold: "wellbeing score 1ポイント以上向上"
    sustainability: "効果が2週間継続"

statistical_analysis:
  significance_test: "paired t-test"
  confidence_level: "95%"
  effect_size: "Cohen's d"
  practical_significance: "日常生活での体感的価値"

## システム・メンテナンス・スケジュール

### 定期メンテナンス・カレンダー
**Scheduled Maintenance Windows**：
```yaml
maintenance_schedule:
  daily_maintenance:
    morning_checkin:
      duration: "10分"
      activities: ["体調確認", "エネルギーレベル評価", "1日の優先度設定"]
      
    evening_shutdown:
      duration: "15分" 
      activities: ["1日の振り返り", "ストレス・リリース", "翌日準備"]
  
  weekly_maintenance:
    week_retrospective:
      duration: "30分"
      activities: ["週間目標達成度評価", "ストレス・パターン分析", "来週計画"]
      
    deep_recovery:
      duration: "2-3時間"
      activities: ["趣味時間", "社会的活動", "完全リラックス"]
  
  monthly_maintenance:
    comprehensive_review:
      duration: "1時間"
      activities: ["月間メトリクス分析", "目標・戦略見直し", "システム改善"]
      
    system_optimization:
      duration: "半日"
      activities: ["環境整備", "ツール・習慣の見直し", "新しい実験計画"]
  
  quarterly_maintenance:
    major_system_upgrade:
      duration: "1日"
      activities: ["人生・キャリア目標見直し", "大きな環境変化検討", "スキル・関係性の棚卸し"]

## インシデント対応プロセス

### ストレス・インシデントの分類と対応
**Incident Severity Levels**：
```python
class MentalHealthIncident:
    SEVERITY_LEVELS = {
        'P0_CRITICAL': {
            'description': '重大なメンタルヘルス危機',
            'symptoms': ['自傷・自殺念慮', '重度のパニック発作', '現実認識困難'],
            'response_time': '即座（5分以内）',
            'escalation': ['医療機関受診', '緊急連絡先への連絡', '専門家介入']
        },
        'P1_MAJOR': {
            'description': '深刻なストレス状態',
            'symptoms': ['持続的不安', '睡眠・食事困難', '社会機能低下'],
            'response_time': '当日中',
            'escalation': ['信頼できる人への相談', 'カウンセリング予約', '業務調整']
        },
        'P2_MODERATE': {
            'description': '中程度のストレス増加',
            'symptoms': ['集中力低下', 'イライラ増加', '疲労感蓄積'],
            'response_time': '24-48時間以内',
            'escalation': ['セルフケア強化', 'サポート・ネットワーク活用']
        },
        'P3_MINOR': {
            'description': '軽微なストレス要因',
            'symptoms': ['軽度の不安', '一時的な集中困難', 'やる気の低下'],
            'response_time': '1週間以内',
            'escalation': ['日常的対処法', '予防的措置の見直し']
        }
    }
    
    def classify_incident(self, symptoms, duration, impact):
        """症状・継続期間・影響度からインシデント・レベルを判定"""
        severity_score = self.calculate_severity(symptoms, duration, impact)
        
        if severity_score >= 90:
            return 'P0_CRITICAL'
        elif severity_score >= 70:
            return 'P1_MAJOR'
        elif severity_score >= 40:
            return 'P2_MODERATE'
        else:
            return 'P3_MINOR'

## レジリエンス・バックアップ・システム

### 多層防御によるメンタルヘルス保護
**Defense in Depth Strategy**：

## Personal CI/CD Pipeline

### 継続的統合（Continuous Integration）
**Daily Integration of Self-Improvements**：
```yaml
personal_ci_pipeline:
  triggers:
    - daily_reflection_commit
    - weekly_goal_update
    - monthly_metric_review
    
  stages:
    code_quality_check:
      - habit_consistency_check: "習慣の実行率 > 80%"
      - goal_alignment_test: "行動と目標の整合性確認"  
      - wellbeing_metric_validation: "メンタルヘルス指標の正常範囲確認"
      
    integration_tests:
      - work_life_balance_test: "仕事・プライベートの調和確認"
      - relationship_health_test: "人間関係の質的評価"
      - stress_resilience_test: "ストレス対処能力の検証"
      
    performance_tests:
      - cognitive_performance_benchmark: "認知能力のベースライン比較"
      - productivity_regression_test: "生産性指標の低下検出"
      - happiness_index_monitoring: "主観的幸福度の追跡"

  notifications:
    success: "今日も順調に成長中！"
    warnings: "一部指標に注意が必要です"
    failures: "緊急の調整が必要です"

## 個人環境のコード化

### 環境設定の自動化・再現可能性
**Reproducible Personal Environment**：
```yaml
# personal_environment.yml
personal_infrastructure:
  physical_workspace:
    desk_setup:
      monitor_configuration: "dual_4k_setup"
      lighting: "adjustable_led_with_circadian_rhythm"
      ergonomics: "standing_desk_with_ergonomic_chair"
      
  digital_environment:
    productivity_stack:
      - task_management: "todoist_with_gtd_methodology"
      - note_taking: "obsidian_with_zettelkasten"
      - time_tracking: "toggl_with_pomodoro_integration"
      
    monitoring_tools:
      - health_tracking: "apple_health_with_custom_shortcuts"
      - mood_tracking: "daylio_with_custom_metrics"
      - productivity_analytics: "rescuetime_with_custom_goals"
  
  mental_environment:
    daily_routines:
      morning:
        - meditation: "10min_headspace_or_calm"
        - journaling: "5min_gratitude_plus_intentions"
        - goal_review: "daily_priorities_alignment"
        
      evening:
        - reflection: "what_went_well_what_to_improve"
        - planning: "tomorrow_top_3_priorities"
        - shutdown_ritual: "digital_sunset_plus_relaxation"
    
    weekly_routines:
      - deep_work_blocks: "3x 4hour_sessions"
      - social_connections: "2x meaningful_interactions"
      - learning_time: "5hours_skill_development"
      - recovery_time: "full_day_rest_and_recharge"

deployment_strategy:
  blue_green_deployment: "新しい習慣を段階的に導入し、並行運用"
  rollback_plan: "効果のない変更の迅速な撤回手順"
  monitoring: "変更の影響を継続的に監視"

## 個人パフォーマンスSLI/SLO

### Service Level Indicators（SLI）
**Personal Performance Measurements**：
```python
class PersonalSLI:
    def calculate_availability_sli(self):
        """個人の「可用性」= 正常に機能している時間の割合"""
        total_hours = 24 * 7  # 1週間
        functional_hours = total_hours - self.get_downtime_hours()
        return functional_hours / total_hours
    
    def get_downtime_hours(self):
        """機能停止時間（病気・極度疲労・バーンアウト状態）"""
        return self.sick_hours + self.burnout_hours + self.severe_stress_hours
    
    def calculate_performance_sli(self):
        """パフォーマンス = タスク完了時間の目標達成率"""
        completed_tasks = self.get_completed_tasks_this_week()
        on_time_tasks = [t for t in completed_tasks if t.completion_time <= t.estimated_time]
        return len(on_time_tasks) / len(completed_tasks) if completed_tasks else 0
    
    def calculate_error_rate_sli(self):
        """エラー率 = ミス・やり直しが必要だった作業の割合"""
        total_work_items = self.get_total_work_items()
        error_items = self.get_items_requiring_rework()
        return len(error_items) / len(total_work_items) if total_work_items else 0

class PersonalSLO:
    """Service Level Objectives - 個人パフォーマンス目標"""
    
    AVAILABILITY_TARGET = 0.95  # 95%の時間で正常機能
    LATENCY_TARGET = 0.90       # 90%のタスクが期限内完了
    ERROR_RATE_TARGET = 0.05    # エラー率5%以下
    WELLBEING_TARGET = 7.0      # 10点満点で7点以上の主観的満足度

    def evaluate_slo_compliance(self, sli_metrics):
        """SLO達成状況の評価"""
        compliance = {
            'availability': sli_metrics.availability >= self.AVAILABILITY_TARGET,
            'performance': sli_metrics.performance >= self.LATENCY_TARGET,
            'quality': sli_metrics.error_rate <= self.ERROR_RATE_TARGET,
            'wellbeing': sli_metrics.wellbeing_score >= self.WELLBEING_TARGET
        }
        
        overall_health = sum(compliance.values()) / len(compliance)
        return {
            'individual_metrics': compliance,
            'overall_health_score': overall_health,
            'requires_attention': overall_health < 0.75
        }

## 個人エラー・バジェット管理

### エラー・バジェットの概念適用
**Planned Downtime vs Unplanned Incidents**：
```python
class PersonalErrorBudget:
    def __init__(self, monthly_availability_target=0.95):
        self.target_availability = monthly_availability_target
        self.total_hours_per_month = 24 * 30
        self.allowed_downtime = self.total_hours_per_month * (1 - monthly_availability_target)
        
    def calculate_current_budget(self):
        """現在のエラー・バジェット残量"""
        used_downtime = self.get_unplanned_downtime_this_month()
        remaining_budget = self.allowed_downtime - used_downtime
        
        return {
            'total_budget': self.allowed_downtime,
            'used_budget': used_downtime,
            'remaining_budget': remaining_budget,
            'budget_utilization': used_downtime / self.allowed_downtime,
            'status': self.get_budget_status(remaining_budget)
        }
    
    def get_budget_status(self, remaining_budget):
        """バジェット状況の評価"""
        utilization = 1 - (remaining_budget / self.allowed_downtime)
        
        if utilization < 0.5:
            return 'healthy'
        elif utilization < 0.8:
            return 'caution'  
        elif utilization < 1.0:
            return 'critical'
        else:
            return 'exceeded'
    
    def recommend_actions(self, budget_status):
        """バジェット状況に応じた推奨アクション"""
        recommendations = {
            'healthy': [
                "新しい挑戦に取り組める余裕あり",
                "スキル向上・成長機会を積極的に"
            ],
            'caution': [
                "予防的メンテナンスを強化",
                "ストレス管理をより意識的に"
            ],
            'critical': [
                "新しい取り組みは一時停止",
                "回復・安定化にフォーカス",
                "サポート・システム活用"
            ],
            'exceeded': [
                "緊急事態：即座の介入が必要",
                "専門家サポートの検討",
                "環境・負荷の根本的見直し"
            ]
        }
        return recommendations.get(budget_status, ["状況を詳しく分析してください"])