HRV in Corporate Health Management

Trust in Performance and Health

easy - valid - scaleable

HRV Measurement

  • Anonymous do-it-yourself-measurements in professional and private life
  • Individual support through experienced professionals
  • Real-time-health-communication (also during pandemics)
  • High performer stay efficient
  • Evaluation of interventions
  • Comprehensive stress analysis
  • Personal health assistant for every employee
  • Objective assessment of human capital
  • Identification of hazards and resources
  • Reduction of error rates
  • Valid informationen for people in authority
  • Reduction of times absent and fluctuation

Healthy Staff = Healthy Company

Thanks to HRV measurements, employees’ performances can increase and health within the company can improve.

Absent days due to mental illness and stress disorders are on the rise. HRV measurements visualise the personal state of health on a physical and mental level and provide solutions to processing stress, regeneration ability and risk of exhaustion. It is interesting to see where you stand compared to others. HRV measurements for employees – voluntary and anonymous – motivate people to advocate for their own health. Individual recommendations encourage people to get engaged. The first and subsequent measurements strengthen the resilience within the company sustainably.

Increase productivity, Decrease costs

  • Capture the staff’s state of health in a pooled and anonymous way and show it as a new parameter in BGM.
  • Plan preventative measures efficiently and adjust them according to the resources that need strengthening.
  • Support the employee where it’s effectively needed.
  • Purposefully reduce excessive stress

The company gains resilience, becomes more confident in dealing with pressure and can brace itself for challenges.

How can HRV be applied in Corporate Health Management?

The pivotal point of your company’s success is the health of your staff!
We’re happy to inform you on how you can apply our solutions optimally for you and your clients.

  • User-friendliness: Handling the measurement devices (no turning on/off, data upload in a few seconds, logging of activities via app, automatic synchronisation of measurement and activity data).
  • Analysis effort: No processing by experts needed. Immediate analysis of up to 150 cardiac output and HRV data, health determinants and lifestyle factors.
  • Accuracy: Immediate analysis of 288 five-minute periods of measurement time in the form of an intuitively perceptible “performance graph” to reflect different “energy levels”.
  • Extent: From the 5-minute short analysis, to the do-it-yourself 24h measurement, to the medical detail analysis including respiration, screening of cardiac arrhythmias etc. and personal coaching by experts (doctor, psychologist, coach, therapist).
  • Sustainability: Motivation system with recommendations, reward system in the form of special progress charts.
  • Price: Unbeatable cost-benefit-ratio (e.g. total cost for a staff of 100 is €30,- per employee for two measurements/employee/year including hardware and electrodes).

HRV measurements recommended for occupational medicine

HRV measurements are recommended for company doctors and occupational medicine. Autonom Health – first provider of do-it-yourself-health diagnostics – offers medically founded and valid HRV measurements. The 24h mini-ECG evaluates over 100,000 data. The sampling rate of 1,000Hz meets the cardiologists’ and occupational physicians’ requirements. Including high-end data protection and data security.

“Valid and reproducible analyses of heart rate variability are calculated by mathematical coherences of the respective figures and facts at hand of one or more measurements. The results have to be correlated to the respective age and gender groups and are to be calculated and documented using understandable algorithms that are based on physiological regulations and the results of validated scientific publications.”

(excerpt from “Herzratenvariabilität, Das HRV-Praxis-Lehrbuch” by A. Lohninger, 2017)

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