Rehabilitation Analyzer

The skill is automatically triggered in the following situations:

1. User runs /rehab progress to view rehabilitation progress
2. User runs /rehab analysis to perform rehabilitation analysis
3. User runs /rehab trends to view trend analysis
4. User runs /rehab report to generate a rehabilitation report

Execution Steps

Step 1: Data Reading

Read rehabilitation data files:

• data/rehabilitation-tracker.json - Main rehabilitation profile
• data/rehabilitation-logs/YYYY-MM/YYYY-MM-DD.json - Daily training logs

Data Validation:

• Check if files exist
• Verify data structure integrity
• Confirm sufficient data points for analysis (recommend at least 3 assessments or 10 days of training records)

Step 2: Functional Assessment Trend Analysis

Range of Motion (ROM) Analysis:

- Analyze ROM measurements at different time points
- Calculate ROM improvement rate (degrees/week)
- Identify ROM plateaus or regression
- Predict time to reach target ROM
- Compare against target range

Muscle Strength Improvement Analysis:

- Track muscle strength grade changes (MMT score)
- Identify strength improvement patterns
- Compare recovery rates across different muscle groups
- Assess muscle strength imbalances

Balance Function Analysis:

- Balance test score trends
- Single-leg stance time improvement
- Balance stability assessment
- Fall risk changes

Step 3: Pain Pattern Analysis

Pain Temporal Analysis:

- Analyze morning pain trends
- Analyze post-activity pain trends
- Identify pain exacerbation/relief patterns
- Correlate pain with training intensity

Pain Trigger Factor Identification:

- Relationship between specific exercises and pain
- Correlation between training intensity and pain
- Relationship between activity type and pain
- Impact of timing factors on pain

Step 4: Training Adherence Calculation

Adherence Metrics:

Adherence = (Actual Training Sessions / Planned Training Sessions) x 100%

Analysis Dimensions:

• Weekly adherence
• Monthly adherence
• Overall adherence
• Adherence by training type

Step 5: Goal Achievement Assessment

Goal Progress Tracking:

• Calculate completion percentage for each goal
• Estimate goal achievement timeline
• Identify lagging goals
• Provide goal adjustment recommendations

Step 6: Rehabilitation Phase Assessment

Current Phase Analysis:

• Phase goal completion status
• Readiness to progress to the next phase
• Phase transition recommendations

Step 7: Report Generation

Output includes:

• Rehabilitation progress summary
• Functional improvement trends
• Pain control status
• Training adherence evaluation
• Goal achievement assessment
• Phase progression recommendations
• Personalized recommendations

Output Format

Rehabilitation Progress Report Structure

# Rehabilitation Progress Report
**Report Date**: YYYY-MM-DD
**Rehabilitation Duration**: X days
**Current Phase**: Phase X - Phase Name

## 1. Rehabilitation Progress Summary

[Overall Progress Rating: Excellent/Good/Fair/Needs Improvement]
- Rehabilitation Duration: X days (Week X)
- Completed Training Sessions: X
- Training Adherence: X%
- Current Phase Progress: X%

## 2. Functional Improvement Trends

### Range of Motion (ROM)
- [Joint Name] [Movement Type]: Baseline X deg -> Current X deg -> Improvement X deg
- Improvement Rate: X deg/week
- Estimated Time to Goal: X weeks
- Trend Analysis: [Improvement trend description]

### Muscle Strength Assessment
- [Muscle Group]: Baseline X/5 -> Current X/5 -> Improvement X grade(s)
- Strength Improvement Pattern: [Description]
- Strength Balance: [Assessment]

### Balance Function
- [Test Type]: Baseline X -> Current X -> Improvement X
- Balance Stability: [Assessment]
- Fall Risk: [Assessment]

## 3. Pain Control Status

- Average Pain Level: X/10
- Pain Trend: [Improving/Stable/Worsening]
- Pain Pattern: [Description]
- Trigger Factors: [Identified triggers]
- Pain Control Recommendations: [Recommendations]

## 4. Training Adherence

- Overall Adherence: X%
- Planned Sessions: X
- Completed Sessions: X
- Adherence Rating: [Excellent/Good/Fair/Needs Improvement]
- Missed Session Analysis: [If applicable]

## 5. Goal Achievement Status

### Achieved Goals (X)
- Goal 1: [Description] - Achieved on: YYYY-MM-DD
- ...

### In-Progress Goals (X)
- Goal 1: [Description] - Current Progress: X% - Estimated Achievement: YYYY-MM-DD
- ...

### Lagging Goals (X)
- Goal 1: [Description] - Current Progress: X% - Needs Attention

## 6. Rehabilitation Phase Progress

**Current Phase**: Phase X - [Phase Name]
- Phase Goals Completed: X/X
- Phase Progress: X%
- Phase Duration: X weeks
- **Phase Rating**: [Rating]

**Ready to Progress to Next Phase**: [Yes/No]
- [Reasons for readiness] / [Items requiring further effort]

## 7. Personalized Recommendations

### Training Recommendations
- [Specific training recommendations]

### Goal Adjustment Recommendations
- [Goal adjustment recommendations]

### Phase Transition Recommendations
- [Phase transition recommendations]

### Precautions
- [Items to watch for]

## 8. Next Assessment

**Next Assessment Date**: YYYY-MM-DD
**Assessment Focus**: [Key assessment items]

Brief Progress Report

## Rehabilitation Progress Brief

**Overall Progress**: Good
**Rehabilitation Duration**: Week X (X days)
**Phase**: Phase X - [Phase Name]

**Functional Improvement**:
- ROM: +X deg (improvement rate X deg/week)
- Muscle Strength: Improved X grade(s)
- Balance: Improved X%

**Pain Control**: Average X/10 ([Trend])
**Training Adherence**: X% ([Rating])
**Goal Achievement**: X/X (X%)

**Current Phase**: X/X goals completed
**Next Phase Readiness**: [Yes/No]

**Recommendation**: [1-2 key recommendations]

Data Sources

Main Data File

• File Path: data/rehabilitation-tracker.json
• Read Fields:
  • user_profile - User profile and basic rehabilitation information
  • rehabilitation_goals - Rehabilitation goal list
  • exercise_log - Training log
  • functional_assessments - Functional assessment records
  • phase_progression - Phase progression records
  • pain_diary - Pain diary
  • statistics - Statistical data

Log Data Files

• File Path: data/rehabilitation-logs/YYYY-MM/YYYY-MM-DD.json
• Read Fields:
  • daily_summary - Daily training summary
  • exercise_sessions - Training details
  • pain_entries - Pain records
  • assessments - Assessment records
  • notes - Daily notes

Analysis Algorithms

1. Improvement Trend Analysis

Linear Regression Analysis:

Use least-squares method to fit functional improvement trends
Improvement Rate = (Current Value - Baseline Value) / Time Interval

Improvement Pattern Recognition:

• Linear improvement: Steady, continuous improvement
• Stepwise improvement: Rapid improvement following a plateau
• Plateau: Improvement stagnation
• Regression: Functional decline (requires attention)

2. Pain Temporal Analysis

Moving Average Calculation:

7-Day Moving Average Pain = sum(pain over last 7 days) / 7

Pain Trend Determination:

• Improving: Pain score decreased by >=20%
• Stable: Pain score change <20%
• Worsening: Pain score increased by >=20%

3. Adherence Calculation

Overall Adherence = (Actual Training Days / Planned Training Days) x 100%

Training Type Adherence = (Actual Completions of Type / Planned Completions of Type) x 100%

Adherence Rating:

• Excellent: >=90%
• Good: 75-89%
• Fair: 60-74%
• Needs Improvement: <60%

4. Goal Achievement Prediction

Linear Extrapolation:

Predicted Time = Current Date + ((Target Value - Current Value) / Improvement Rate)

Factors Considered:

• Recent improvement rate
• Plateau history
• Training adherence

5. Phase Transition Readiness Assessment

Readiness Score:

Readiness = (Phase Goals Achieved / Total Phase Goals) x 100%

Readiness >= 80%: Recommend progressing to next phase
Readiness 60-79%: May consider progressing to next phase with caution
Readiness < 60%: Recommend continuing current phase

Security and Privacy

Data Security Principles

1. Local Storage

   • All rehabilitation data is stored only on the user's local device
   • Not uploaded to any cloud servers
   • Not shared with third parties

2. Privacy Protection

   • Personal health information is strictly confidential
   • Data files do not contain personally identifiable information
   • Users have full control over data access permissions

3. Data Integrity

   • Original data is not modified
   • Analysis results are based on actual data
   • Supports data export and backup

Medical Safety Boundaries

What the system CANNOT do:

• Does not provide specific rehabilitation exercise prescriptions
• Does not replace professional rehabilitation therapist guidance
• Does not diagnose injuries or complications
• Does not modify rehabilitation phase plans
• Does not predict rehabilitation prognosis timelines
• Does not handle acute pain or injuries

What the system CAN do:

• Provides data analysis and trend identification
• Provides progress tracking and goal management
• Provides general rehabilitation recommendations
• Provides professional rehabilitation referral reminders
• Records training and assessment data
• Generates rehabilitation progress reports

Important Notice:

• All rehabilitation training plans should follow therapist guidance
• Any worsening pain or functional regression should prompt immediate medical attention
• Regular professional assessments are key to successful rehabilitation
• System recommendations are for reference only and do not replace professional judgment

Error Handling

Data Reading Errors

Error Type 1: File Not Found

Error: Rehabilitation data file not found. Please use /rehab start to begin rehabilitation tracking first.
Action: Guide the user to start rehabilitation recording.

Error Type 2: Insufficient Data

Error: Insufficient data. At least 3 functional assessments or 10 days of training records are required to generate an analysis report.
Current Data: X assessments, X days of training records.
Action: Recommend the user continue recording more data.

Error Type 3: Data Structure Error

Error: Data file structure is abnormal. Please check data integrity.
Action: Recommend the user reinitialize the rehabilitation profile.

Analysis Process Errors

Error Type: Calculation Exception

Error: An exception occurred during data analysis. Please try again later.
Action: Log the error; provide basic data display.

Output Generation Errors

Error Type: Report Generation Failed

Error: Report generation failed. Please try simplifying query conditions or contact technical support.
Action: Provide a simplified report or raw data export.

Usage Examples

Example 1: View Rehabilitation Progress

User Input:

/rehab progress

Skill Execution:

1. Read rehabilitation-tracker.json
2. Read rehabilitation logs from the past 30 days
3. Analyze functional improvement trends
4. Calculate training adherence
5. Assess goal achievement status
6. Generate progress report

Output:

# Rehabilitation Progress Report

## Rehabilitation Progress Summary
Overall Progress: Good
Rehabilitation Duration: Week 6 (36 days)
Current Phase: Phase 3 - Strengthening

## Functional Improvement
- Knee Flexion: 30 deg -> 120 deg (+90 deg)
- Knee Extension: -10 deg -> 0 deg (+10 deg)
- Quadriceps Strength: 3/5 -> 4/5 (Improved 1 grade)
- Single-Leg Stance: 5 sec -> 30 sec (+25 sec)

## Pain Control
- Average Pain: 1.5/10 (Well controlled)
- Pain Trend: Stable

## Training Adherence: 92% (Excellent)

## Goal Achievement: 8/14 (57%)
- Achieved: 8
- In Progress: 5
- Lagging: 1

## Phase Progress
Phase 3 Progress: 2/5 goals completed (40%)
Next Phase Readiness: Needs further effort

Recommendation: Maintain current training intensity; focus on quadriceps strengthening exercises

Example 2: Analyze Functional Improvement Trends

User Input:

/rehab trends rom

Skill Execution:

1. Extract all ROM assessment records
2. Describe ROM improvement curve
3. Calculate improvement rate
4. Predict time to reach target
5. Identify improvement pattern

Output:

# Range of Motion (ROM) Trend Analysis

## Knee Flexion
Improvement Trend: Good

Timeline:
- 5/15: 30 deg (Baseline)
- 5/30: 70 deg (+40 deg)
- 6/15: 100 deg (+30 deg)
- 6/20: 120 deg (+20 deg)

Improvement Rate: 8.6 deg/week
Target: 135 deg
Estimated Achievement: 2025-08-01 (2 more weeks)
Trend: Continuous improvement

## Knee Extension
Target achieved

Timeline:
- 5/15: -10 deg (Baseline)
- 6/10: 0 deg (Target achieved)
- 6/20: 0 deg (Maintained)

Improvement Rate: 2.5 deg/week
Target: 0 deg
Achievement Date: 2025-06-10
Trend: Maintaining target

## Recommendations
- Knee flexion progressing well; continue current approach
- Maintain extension exercises to prevent flexion contracture
- Target flexion goal expected within 2 weeks

Example 3: Assess Pain Patterns

User Input:

/rehab analysis pain

Skill Execution:

1. Extract all pain records
2. Analyze pain temporal changes
3. Identify pain trigger factors
4. Assess pain control effectiveness

Output:

# Pain Pattern Analysis

## Pain Trend
Overall Trend: Improving

- Baseline Pain: 5/10
- Current Pain: 2/10
- Improvement: 3 points (60% improvement)

## Temporal Pattern
- Morning Pain: 1/10 (Mild)
- Post-Activity Pain: 2/10 (Mild)
- Resting Pain: 0/10 (None)

## Trigger Factor Identification
- Main Triggers: Prolonged sitting, stairs
- Pain-Aggravating Activities: Descending stairs, deep squats
- Relief Factors: Rest, ice, elevation

## Training-Related Pain
- Average Pain During Training: 1.2/10 (Safe range)
- Post-Training Pain: 2/10 (Resolves quickly)
- Training adherence unaffected by pain

## Recommendations
- Pain is well controlled; maintain current training intensity
- Rest and apply ice after training
- Avoid pain-aggravating activities (deep squats, descending stairs)
- If pain exceeds 4/10, seek medical evaluation promptly

Correlation Analysis

Correlation with Exercise Module

Correlation Analysis:

• Relationship between rehabilitation training and exercise capacity recovery
• Relationship between rehabilitation training intensity and heart rate changes
• Correlation between functional improvement and daily activity levels

Example:

User runs /rehab analysis correlation fitness
Skill reads:
- rehabilitation-tracker.json
- fitness-tracker.json
- Analyzes correlation between rehabilitation training and exercise metrics

Correlation with Sleep Module

Correlation Analysis:

• Relationship between training intensity and sleep quality
• Relationship between pain levels and sleep duration
• Recovery-phase sleep needs analysis

Correlation with Medication Module

Correlation Analysis:

• Pain medication usage trends
• Relationship between medication and training intensity
• Pain control and medication adherence