Key metrics
|
Number of participants
|
78 subjects
|
|
Average age
|
42 years
|
|
Percentage men
|
62%
|
|
Total number of measurements
|
599
|
|
Median number of measurements / participant
|
5
|
|
Average number of measurements / participant
|
8
|
|
People with atrial fibrillation (AF)
|
0 (0%)
|
|
People with other cardiac arrhythmia’s
|
5 (6.4%)
|
|
Total number of heartbeats registered
|
38,496
|
Demography
The following section addresses data related to the background of the enrolled participants. Data is coming from the gender, the registered age, the country of origin and the type of smartphone the user is handling.
|
Avg age man:
|
44.5
|
|
Avg age women:
|
38.7
|
|
Oldest male participant:
|
61.8
|
|
Oldest female participant:
|
64.9
|
|
Total number of participants:
|
78
|
|
Average age:
|
42 years
|
|
Participants >40 years:
|
62%
|
|
Participants >60 years :
|
3%
|
|
Country with most users:
|
BE
|
|
Total countries:
|
15
|
|
Most popular device:
|
Apple
|
|
Percentage iOS:
|
46%
|
MEDICAL HISTORY
When users have performed their first measurement they are prompted with a screen that allows them to enter a questionnaire. This questionnaire consists of a set of questions that relate to cardiovascular risk factors. The questionnaire is optional and participants can skip these questions if they want. The table below shows a high-level overview of the cardiovascular risk profile of this population.
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|
History of Heart Failure
|
0
|
|
History of Diabetes
|
0
|
|
History of Artery Disease
|
0
|
|
History of AF
|
0
|
|
History of hypertension
|
0
|
|
History of Stroke
|
0
|
|
Already takes a bloodthinner
|
0
|
|
Amount of filled in questionnaires
|
0
|
|
Amount of blank questionnaires
|
78
|
Enrollment
The following data provides insight in the enrollment details of the population. This is relevant information to identify peak moments when participants activated their subscription.
|
Peak activation - day:
|
2021-03-02
|
|
Peak activation - Time (UTC):
|
14
|
|
Peam measurements (UTC):
|
12-2 PM
|
|
Total number of measurements received:
|
599
|
|
Max number of tot. measurements / day:
|
31
|
|
Most compliant user (%):
|
75%
|
|
Average number of measurements/user:
|
8
|
|
Average compliance (%):
|
13%
|
Diagnostics
This section will cover the findings based on heart rhythm disorders. The table on the left represents the amount of measurements received and the corresponding confirmation of heart rhythms indicated by the FibriCheck Telemonitoring Center. The table on the right represents the findings of symptoms throughout all measurements.
|
Amount of people with Atrial Fibrillation:
|
0
|
|
Amount of people with other cardiac arrhythmia’s:
|
5
|
|
Average heart rate of non-AF people (bpm):
|
64
|
|
Average heart rate during AF (bpm):
|
NaN
|
|
Measurements with symptoms (%):
|
23%
|
|
Most common symptom:
|
fatigue
|
|
Heart rhythm
|
Frequency
|
%
|
|
sinus
|
508
|
84.8
|
|
quality_to_low
|
71
|
11.9
|
|
extrasystoles_frequent
|
8
|
1.3
|
|
tachycardia
|
6
|
1.0
|
|
bradycardia
|
2
|
0.3
|
|
extrasystoles_big_episode
|
2
|
0.3
|
|
increased_hrv
|
2
|
0.3
|
|
Symptoms
|
Frequency
|
%
|
|
no_symptoms
|
459
|
76.6
|
|
NA
|
74
|
12.4
|
|
fatigue
|
27
|
4.5
|
|
other
|
26
|
4.3
|
|
palpitations
|
5
|
0.8
|
|
shortness_of_breath
|
5
|
0.8
|
|
chest_pains
|
1
|
0.2
|
|
confused
|
1
|
0.2
|
|
lightheaded
|
1
|
0.2
|
Symptoms during sinus rhythms
|
Symptoms
|
Frequency
|
%
|
|
no_symptoms
|
195
|
75.6
|
|
NA
|
36
|
14.0
|
|
fatigue
|
15
|
5.8
|
|
other
|
10
|
3.9
|
|
confused
|
1
|
0.4
|
|
shortness_of_breath
|
1
|
0.4
|
Symptoms during non-AF rhythms
|
Symptoms
|
Frequency
|
%
|
|
no_symptoms
|
308
|
77.6
|
|
NA
|
47
|
11.8
|
|
fatigue
|
18
|
4.5
|
|
other
|
14
|
3.5
|
|
palpitations
|
4
|
1.0
|
|
shortness_of_breath
|
4
|
1.0
|
|
chest_pains
|
1
|
0.3
|
|
confused
|
1
|
0.3
|
Symptoms during AF rhythms
|
Symptoms
|
Frequency
|
%
|
Signal Quality Analysis
When people are using FibriCheck there is an important element related to the usability of the application. The measurements conducted with the smartphone are sensitive to possible sources of noise. If this occurs the signals cannot be analysed for diagnostic purposes. On average the insufficient quality range on a population is around
10%. The results obtained in this project can be found in the table on the left. The table in the middle represents how easy it was for users to conduct a measurement. The attempts reflect how many times a measurement was restarted by the user before it was succesful. On average a number of
85% is observed. A possible reason for insufficient quality could be related to the contextual information. The table on the right illustrtes the relation between the total amount of insufficient singal quality compared to the context activity the users indicated when the measurement was conducted.
|
Average % of insufficient quality:
|
11.37%
|
|
Minimum % of insufficient quality:
|
0%
|
|
Maximum % of insufficient quality:
|
100%
|
|
Meas. attempts
|
Percentage (%)
|
|
1
|
77.1
|
|
2
|
8.2
|
|
3
|
3.0
|
|
4
|
1.3
|
|
5
|
0.2
|
|
7
|
0.2
|
|
NA
|
10.0
|
|
Activity context
|
Insufficient quality distribution (%)
|
|
sitting
|
84.5
|
|
NA
|
8.5
|
|
standing
|
5.6
|
|
walking
|
1.4
|
|
exercising
|
0.0
|
|
other
|
0.0
|
|
sleeping
|
0.0
|
Rhythm recordings
These graphs highlight some of the use cases identified in this project. The graphs represent the all the measurement data from a subject and visualised on timeline (days). The y-axis reflects the heart-rate of each measurement and the color reflects the corresponding heart rhythm. Green indicates a regular heart rhythm, yellow indicates unclassified heart rhythms (typically ectopic heart beats), red illustrates possible atrial fibrillation findings and blue indicates measurements of insufficient signal quality.
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