Heart Rate Alarms

Heart Rate alarms use measured heart rate values to detect abnormal physiology patterns. The app supports three heart-rate checks that can run together.

How it works

flowchart TD
    A[Incoming heart rate value] 
    A --> H{Measured HR outside of thresholds?}
    H --> |Yes| F[Calculate Adaptive threshold from short term rolling average]
    H --> |No | C[Calculate short term rolling average]
    C --> E{Measured HR outside of Adaptive Thresholds?}
    E -->|Yes| F[Heart Rate algorithm ALARM]
    E --> |No| D[Calculate long term rolling average]
    D --> K{Long Term Average HR outside of Thresholds?}
    K -->|Yes| F[Heart Rate algorithm ALARM]
    K -->|No| G[Heart Rate algorithm OK]

The Heart Rate detector is made of three separate checks that can run in parallel:

• Simple threshold: alarms if current heart rate is below minimum or above maximum.
• Adaptive threshold: compares current heart rate against a short rolling average plus or minus an offset.
• Rolling average threshold: alarms if the longer rolling average is outside configured limits.

Technical description of each algorithm

1. Simple threshold algorithm

This is the direct high/low bpm check.

• Input: current heart rate sample.
• Alarm condition: current HR < HRThreshMin or current HR > HRThreshMax.
• Best use: clear hard limits, for example very high tachycardia or very low bradycardia.

flowchart LR
    A[Current HR sample] --> B{HR < HRThreshMin?}
    B -->|Yes| C[Simple HR ALARM]
    B -->|No| D{HR > HRThreshMax?}
    D -->|Yes| C
    D -->|No| E[Simple HR OK]

2. Adaptive threshold algorithm

This tracks a short rolling average and creates a moving alarm band around it.

• Input: current HR and short-window average.
• Dynamic limits:
  • lower limit = adaptive_average - HRAdaptiveAlarmThresh
  • upper limit = adaptive_average + HRAdaptiveAlarmThresh
• Alarm condition: current HR outside the dynamic limits.
• Best use: detect rapid changes relative to recent baseline, not just fixed absolute values.

3. Average HR algorithm

This monitors a longer rolling average and compares that average against fixed limits.

• Input: long-window rolling average.
• Alarm condition: average HR < HRAverageAlarmThreshMin or average HR > HRAverageAlarmThreshMax.
• Best use: sustained physiological drift rather than brief spikes.

Example: rising HR during a seizure-like event

The table below shows how the adaptive threshold band moves upward as HR rises, while still detecting a rapid jump.

Assumed settings in this example:

• HRAdaptiveAlarmThresh = 20 bpm
• HRThreshMax = 140 bpm
• HRAverageAlarmThreshMax = 115 bpm

flowchart LR
    T0[t0: HR 80, avg 80, band 60-100, all OK] --> T1[t1: HR 90, avg 82, band 62-102, all OK]
    T1 --> T2[t2: HR 104, avg 86, band 66-106, all OK]
    T2 --> T3[t3: HR 124, avg 92, band 72-112, adaptive ALARM]
    T3 --> T4[t4: HR 132, avg 100, band 80-120, adaptive ALARM]
    T4 --> T5[t5: HR 128, avg 108, band 88-128, average-HR ALARM risk]

Interpretation:

• Simple threshold reacts only when fixed min or max limits are crossed.
• Adaptive threshold reacts early to fast changes, then its band follows the trend.
• Average HR reacts later, but is strong for prolonged elevation.

User settings

Practical tuning effect

flowchart LR
    A[Lower HRThreshMin] --> B[Fewer low-heart-rate alarms]
    C[Raise HRThreshMax] --> D[Fewer high-heart-rate alarms]
    E[Shorter adaptive window] --> F[More responsive to rapid changes]
    G[Longer adaptive window] --> H[More stable, less reactive]
    I[Tighter adaptive offset] --> J[More sensitive]
    K[Wider adaptive offset] --> L[Less sensitive]

Important data-source note

Heart-rate detection quality depends on watch sensor quality and data continuity. In practical use, Garmin devices generally provide the most reliable continuous heart-rate data.