From ICU to Snow Slopes: Tracking the Rehabilitation Journey of a Youth Athlete After Spinal Surgery with the Ultrahuman Ring AIR

Understanding Youth Rehab After Surgery

• Rehabilitation (rehab) in youth athletes goes beyond physical healing, involving neuromuscular control, cardiovascular stability, and mental readiness.
• Young athletes are still in the growing process, facing unique challenges due to ongoing physiological changes and academic pressures, making rehabilitation more complex. ¹
• Traditional post-op care has lacked real-world monitoring, limiting the ability to detect day-to-day fluctuations or setbacks. ²

Spinal Trauma and Autonomic Function

• High-impact spinal injuries can impair autonomic nervous system regulation, reducing parasympathetic activity. ³
  
• This often manifests as low HRV and high RHR during the acute phase, with improvements signaling physiological recovery. ⁴

Case

‍Disclosure: Informed consent was obtained from the athlete and her family.

Profile

• The subject is a youth female athlete based in Hokkaido, Japan.
• She competes in both backcountry snowboarding and swimming at the national level.
• Prior to injury, her training regimen included off-piste snow drills and competitive endurance swim sets.

Injury and Monitoring Protocol

• In October 2024, the athlete was involved in a motor vehicle accident, resulting in a fracture-dislocation of the L1 and L2 vertebrae.
  
• Surgical intervention included posterior repair and fixation from L1 to L3, performed one day after the accident.
  
• Pain was managed with paracetamol for 72 hours post-op and a brief course of tramadol.
  

• Continuous monitoring with the Ultrahuman Ring AIR began in December 2024 (10 weeks post-op) and continued through May 2025.
  

• Tracked variables included sleep score, sleep duration, sleep efficiency, sleep heart rate variability (HRV), sleep heart rate (HR), recovery score, and movement score.
  
• Data were smoothed using 14-day rolling averages and analyzed weekly to detect trends and short-term fluctuations.
  
• Contextual notes on pain, medication, and training activity were maintained to interpret physiological changes.
  
• Data were reviewed by a certified sports medicine and rehabilitation clinician to ensure accurate conclusions.
  
• Data analysis was conducted using Python by Ultrahuman Science team members not in direct contact with the athlete. 

Results

Autonomic Function Improved Steadily as Rehab Progressed

• HRV improved consistently from ~30 ms in mid-December to nearly 70 ms by late April, while sleep HR dropped from ~83 bpm to ~65 bpm over the same period.
  
• The increase in HRV and decrease in HR suggested a steady return of autonomic balance and improved cardiovascular efficiency during rehab. ⁵
  
• Physiological improvements closely mirrored the timeline of physical activity progression (Figure 1):
  
  • Late December to early January: Light rehab and water walking began; HRV began rising from initial low levels, while HR showed early decline.
    
  • Mid-January to early February: Swimming drills and aquatic rehab increased; HRV continued to rise steadily while HR plateaued briefly.
    
  • February: Low-intensity snowboarding was introduced; HRV gains plateaued, indicating an adjustment phase as rehab intensity grew.
    
  • March: High-output activity resumed with a snowboarding photoshoot; HRV saw a second sharp rise from mid-March, and HR dropped notably.
    
  • April: School stress introduced a temporary setback, with a flattening of HRV and mild increase in HR.
    
  • May: State-level swim competition completed; HRV reached peak values and HR reached its lowest point, reflecting enhanced cardiovascular readiness and overall recovery

Movement Capacity and Daily Activity Improved in Parallel with Recovery

• Movement score, a composite metric comprising total steps, active calories, active hours and workout frequency, rose from ~55 in mid-December to ~90 by early May, showing a clear upward trend (Figure 2).
  
• Early gains occurred through January, followed by a brief dip in late January-February.
  
• From mid-February onwards, scores steadily improved, peaking near 100 by May.
  
• These increases aligned with reintroduction of functional activity, such as snowboarding and swimming.
  
• Movement trends supported the improvements seen in HRV and RHR, reflecting growing physical independence.

Recovery and Sleep Metrics Showed Greater Variability Across the Timeline

• Recovery score, a composite metric affected by sleep, stress, skin temperature, HR and HRV, was relatively stable in December but dropped sharply in late January, then again in late March to early April (Figure 3).
  
• Partial rebounds occurred in February and late April, but fluctuations persisted across the timeline, indicative of daily changes in physiology during rehab.

• Sleep duration showed an inconsistent pattern, ranging from ~400 to 520 minutes per night on a 14-day rolling average (Figure 4).
  
• A slight upward trend was observed in late December and January, followed by relative stability in February.
  
• From early-April, sleep duration declined; dips coincided with drops in recovery score.
• Unlike HRV and movement, sleep and recovery metrics did not follow a clear upward trajectory, highlighting the potential influence of external stressors.

Conclusion

Key Insights from Continuous Monitoring

• Continuous wearable tracking provided real-time insight into post-surgical rehab beyond clinical assessments.
  
• Timeline overlays of HRV and HR with functional milestones showed a clear relationship between physiological recovery and return to physical activity.
  
• The athlete’s staged return from light rehab to competitive events aligned with directional improvements in autonomic markers.

Autonomic Recovery Reflected in Biomarkers

• HRV rose from ~30 ms to ~70 ms, while RHR declined from ~83 bpm to ~65 bpm over the rehab period.
  
• This pattern reflects healing of autonomic pathways following spinal trauma at L1–L3, consistent with known trends post-injury. ⁴

Variable Recovery and Lifestyle Stressors

• Sleep duration and recovery scores were more variable than HRV or HR.
  
• Early variability was likely due to pain and tramadol use, which can negatively affect sleep quality. ^{6, 7}
  
• Later disruptions in sleep and recovery coincided with academic pressure, highlighting the potential influence of lifestyle stressors on adolescent rehab.

Broader Tools to Support Recovery

• Ultrahuman’s Blood Vision and M1 platforms can complement the Ring AIR by offering additional layers of insight into recovery.
  

• When used alongside Ring AIR, these tools create a powerful ecosystem for tracking physiological, biochemical, and behavioral dimensions of rehab.

Mapping Rehab Trajectories & Predictive Intervention

• This case study illustrates the emerging potential of rehab trajectory mapping, where continuous data across multiple domains is overlaid with real-world events to visualise recovery in motion.
• As more such data accumulates, predictive modeling could help anticipate plateaus, relapses, or maladaptive responses to therapy. This would enable clinicians to course-correct rehab protocols in real time, ensuring more personalized, responsive care.
• Future iterations of this approach could integrate wearable biomarkers with structured rehab programming, academic schedules, and psychosocial factors to develop a holistic, adaptive framework for youth rehab.

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