Annovating.com develops and exploits software to store and analyse fitness tracker data.

Annovating Products is the operating company developing and exploiting the 'selfb' data warehousing software. 

Annovating Consultancy delivers LorAIne and CardAId data analysing tools.  Both software packages apply Deep Learning routines to chase earmarked heart rate patterns related to reduced heart functioning

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At present four processing algorithms are being developed

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For each package, written consent will be required. A push notification on your device will guide you through this process in which you will be asked to fully and unconditionally give consent for the purpose, means and duration of the processing.

The following article of Stanford University School of Medicine reveals the latent power of analysing human metrics. Article Stanford University

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selfb

By subscribing to info@annovating.com you can obtain access to our selfb WebApp.

The selfb App takes care of all relevant data transmission to the filing system. Based on the selected service package client questioning and reply options are facilitated as well as personalized push notifications.

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Next to generally acknowledged vital signs also additional human parameters are of interest taking into account when analysing the data. Also external physical parameters can be taken into account if available.

All of these parametes refer to one or more sensors incorporated in the smartwhatch or its appliances.

Vital signs 

1/ Body temperature
2/ Blood pressure (e.g Omron)
3/ Heart rate (e.g Fitbit)
4/ Respiratory rate

Additional human parameters

1/ Oxygen saturation
2/ End-tidal CO2
3/ Spirometry
4/ Glucose (Nature)
5/ Lactate (Nature)
6/ Na+
7/ K+
8/ Gait speed
9/ Galvanic skin response

Physical parameters

1/ GPS position
2/ Air Quality
3/ External temperature  (e.g Blocks)
4/ Humidity  (e.g Blocks)
5/ Altitude (e.g Blocks)  
6/ Radiation

Annovating Consultancy is liaising with reaserch institutes to identify appropriate sensors and to incorporate them into smartwatch functionality.

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Heart rate variability (HRV) analysis attempts to address cardiac autonomic regulation through quantification of sinus rhythm variability. The sinus rhythm times series is derived from the QRS to QRS (RR) interval sequence of the electrocardiogram (ECG), by extracting only normal sinus to normal sinus (NN) interbeat intervals. Relatively high frequency variations in sinus rhythm reflect parasympathetic (vagal) modulation, and slower variations reflect a combination of both parasympathetic and sympathetic modulation and non-autonomic factors .

The low frequency band (0.04 - 0.15 Hz) includes physiologic oscillations associated with baroreceptor reflexes and the high frequency band (0.15 - 0.40 Hz) encompasses respiratory sinus arrhythmia. The powers in these bands has been used to provide indexes of autonomic function. Such measures must be interpreted with caution, however. As noted, oscillations in the "low" frequency bands appear to be mediated by parasympathetic and sympathetic components, while the "high" frequency power is mediated exclusively by the vagus.he low frequency band (0.04 - 0.15 Hz) includes physiologic oscillations associated with baroreceptor reflexes and the high frequency band (0.15 - 0.40 Hz) encompasses respiratory sinus arrhythmia. The powers in these bands has been used to provide indexes of autonomic function. Such measures must be interpreted with caution, however. As noted, oscillations in the "low" frequency bands appear to be mediated by parasympathetic and sympathetic components, while the "high" frequency power is mediated exclusively by the vagus.

In the figure below the HRV is indicated starting at 0:00 hours and reaching to midnight at 24:00. As can be clearly seen, the HRV tends to be higher during nightly hours. Also very low frequency modulations (bubbles) can be seen especially during early morning hours. 

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