Digital Healthcare - Cardiology in the AI era

About how AI help Cardiology

1. Sani M. Isa
BINUS Graduate Program

2. Digital Health in Cardiology
Heart Rate Variability
FirstbeatTechnology
HRV Analysis Result from Garmin Fenix 6
Opportunities

4. Cardiology in a Digital Age: Opportunities and
Challenges for e-Health: A Literature Review
https://www.mdpi.com/2077-0383/12/13/4278

6. •E-health and telemedicine present significant opportunities for
transforming cardiovascular careby leveraging digital technologies.
•These technologies have the potential to improve patient outcomes
through more efficient monitoring, diagnosis, and treatment processes.
•Optimization of healthcare resources by reducing the need for in-
person visitsand enabling remote patient management.
•Challenges:
•Privacy and Data Security
•Technology Acceptance
•Digital Literacy

8. AI in Heart Failure Management
•AI algorithms enhance early detection, diagnosis, and personalized treatmentplans for heart
failure patients.
•Predictive analytics can forecast disease progression and potential complications.
Wearable Technology
•Wearables provide continuous monitoringof vital signs, aiding in real-time health assessments.
•Devices like smartwatches and biosensors offer valuable datafor managing heart failure
remotely.
Remote Monitoring Benefits
•Improves patient outcomes through proactive management and early intervention.
•Reduces hospital readmissions and healthcare costs.
Challenges and Future Directions
•Data privacy and integration issues.
•Need for robust validation and regulatory frameworks for AI applications

10. •Heart rate variability (HRV) is the slight variation in time
between heartbeats, measured in milliseconds. It's also
known as cycle length variability, R–R variability, or heart
period variability
•It reflects the heart's ability to respond to various
physiological and environmental stimuli, such as stress,
exercise, and sleep
•HRV is influenced by the autonomic nervous system,
specifically the balance between the sympathetic (fight
or flight) and parasympathetic (rest and digest)
branches.
•High HRV typically indicates goodcardiovascular fitness
and resilience to stress, while low HRV can be a marker
of stress, fatigue, or potential health issues.

11. https://digitalhealthcentral.com/why-is-my-heart-rate-variability-hrv-so-low/

12. https://www.researchgate.net/figure/Overview-of-the-methods-of-HRV-analysis-with-examples-of-possible-graphical_fig1_279208616

13. 1.Measures calculated from the intervals between normal heart beats
a.AVNN
Average interval between normal heart beats in milliseconds (ms)
b.SDNN
Standard deviation of N-N intervals in ms(total HRV)
c.SDANN
Standard deviation of 5-min mean values of N-Ns for each 5-minute interval in ms
(circadian HRV)
2.Short-term measures calculated from differences between intervals of
successive normal heart beats.
a.rMSSD
Root mean square of successive differences of normal-to-normal intervals in msor the
average change in interval between any two normal beats
b.pNN50
Percent of successive differences of intervals between normal heart beats >50 ms

14. https://www.researchgate.net/figure/HRV-signal-and-its-power-spectral-density-a-Extracted-HRV-signal-b-PSD-of-HRV_fig6_260121050

15. https://ars.els-cdn.com/content/image/1-s2.0-S0010482519301246-fx1_lrg.jpg
CAD: Coronary artery disease

16. https://www.ncbi.nlm.nih.gov/core/lw/2.0/html/tileshop_pmc/tileshop_pmc_inline.html?title=Cli
ck%20on%20image%20to%20zoom&p=PMC3&id=7779618_fnins-14-609570-g001.jpg

17. •HRV and Stress Prediction: HRV has been extensively used for stress detection and
prediction. Advances in wearable technology and machine learning have enabled more
accurate and real-time stress monitoring
•Cardiovascular Health: HRV is a crucial indicator of autonomic nervous system
function and has been linked to cardiovascular health. Lower HRV is associated with
increased mortality and various cardiovascular diseases such as myocardial infarction,
heart failure, and hypertension.
•Mental Health: HRV has also been investigated in the context of mental health,
particularly in patients with depression, anxiety, and other psychiatric disorders.
•Applications in Various Fields: Beyond stress and cardiovascular health, HRV research
has expanded to include applications in exercise physiology, sleep studies, and
occupational health

22. •The development of miniaturized
sensors and wearable devices has
revolutionized HRV monitoring,
making it more accessible and
affordable.
•These devices allow continuous
and non-invasivemonitoring of
HRV, facilitating its use in both
clinical and everyday settings.
•Improved signal processing
algorithms and machine learning
techniques have enhanced the
accuracy of HRVmeasurements
and their interpretation

24. •FirstbeatTechnologies is a Finnishcompany that
specializes in physiological analytics.
•The company is known for developing sophisticated tools
and services that measure and interpret heart rate
variability (HRV), providing insights into various aspects of
health, performance, and well-being.

25. 1. Wellness & Health Monitoring:
Firstbeat'stechnology is widely used in wellness programs and wearable devices to
monitor stress levels, recovery, sleep quality, and overall well-being. Their analytics help
individuals understand how their lifestyle choices impact their health.
2. Sports & Performance:
In sports, Firstbeatprovides tools to optimize training and recovery. Their technology is
used by professional athletes and teams worldwide to monitor performance, training load,
and recovery, enabling data-driven decisions to enhance athletic performance.
3. Corporate Wellness:
Firstbeatalso offers services aimed at corporate wellness programs. They help companies
monitor and improve employee well-being, which can lead to increased productivity and
reduced healthcare costs.

26. •FirstbeatLife: A service designed for personal well-being that provides detailed insights
into stress, recovery, sleep, and physical activity.
•FirstbeatSports: A platform used by professional sports teams to optimize training, reduce
injuries, and improve overall performance through detailed physiological monitoring.
•Corporate Wellness Solutions: Services tailored for organizations looking to improve
employee well-being through comprehensive health analytics.
•Firstbeathas a global presence, partnering with major brands in the wearable technology
industry, including Garmin, Suunto, and others. Their technology is integrated into millions
of devices worldwide, making their analytics accessible to a broad audience.

30. •Firstbeat’score technology revolves around heart rate variability (HRV) analysis.
•HRV is a key indicator of autonomic nervous system function, which reflects the balance
between stress and recovery.
•The company’s algorithms and models are based on extensive physiological research
and are used in various applications, from consumer wearables to professional-grade
sports equipment.
GarminSamsungHuaweiSuunto

32. Discontinued
Garmin fēnix6 Pro Solar
Advanced Health and Fitness Tracking:
The fēnix6 Pro Solar offers a wide range of health and
fitness tracking features, including:
•Heart rate monitoring (with Pulse Ox sensor for
blood oxygen saturation).
•VO2 max estimation.
•Sleep tracking and stress monitoring.
•Body Battery™energy monitoring, which helps
users manage their energy levels throughout the
day.

55. https://cardiolyse.com/wp-content/themes/cardiolyse/public/images/product-1-new-img.png

56. PenelitianUnggulanBinus2020–2022
1.Dr. Sani Muhamad Isa, S.Si., M.Kom
2.Dr. Eng. Nico Surantha, ST., MT.
3.Prof. Dr. Ir. Edi Abdurachman, MS., M.Sc.
4.Dr. Suharjito, S.Si., MT.

57. Intellectual Property (HAKI)
●Nico Surantha, Sani M. Isa, “HeartO: APLIKASI PEMANTAU DAN
PENDETEKSI GANGGUAN JANTUNG” (On-going Registration to DJKI
via RTTO)

58. Features:
•Daily and Weekly
Health Monitoring
•Sleep Quality and
Heart Disease
Prediction using
Artificial Intelligence
•Recommendation for
your Sleep Behavior
•Consultation
Reservation with Sleep
and Heart Expert
•Medicine Reminder
HeartO

59. Option 1: SCD & Sleep Quality Smart Apps
Business model: Partnership:
Competitor: Revenue Stream
•Subscription-based
mobile apps
•Wearable sensor producer ex:
polar, garmin, etc
•Rumahsakitjantung
•Subscription fee•https://actigraphcorp.com/
•strava

60. Option 2: SCD & Sleep Quality
Smart Apps & wearable sensor
Business model: Partnership:
Competitor: Revenue Stream
•Subscription-based
mobile apps
•Sensor device sales
•Rumahsakitjantung
•Subscription fee
•Device sales revenue
•Garmin
•Polar

61. Option 3: SCD & Sleep Quality
Monitoring as Service
Business model: Partnership:
Competitor: Revenue Stream
•Partnership with IoT
vendor to implement
the data analytics
algorithm
•API Call
•IoT solution
vendor, ex:
Astra
GraphiaIT
•Profit-sharing•Not identified yet

62. Commercialization Plan Summary
NoTitle Mobile appsData
analytics
algorithm
Cloud
Platform
Wearab
le
Sensor
1SCD &
Sleep
Quality Apps
vvvx
2SCD &
Sleep
Quality
wearable
sensor &
apps
vvvv
3 SCD & xvxx
Note:
v = Provided by BINUS
x = Provided by External/industry partner

63. Commercialization Discussion
with Astra GraphiaIT

65. Binus–Astra GraphiaIT
Agreements
●Binuswill provide the SCD & Sleep Monitoring service
in the Cloud
●Astra GraphiaIT will consume the service on their
platform using API (Application Programming
Interface) Call
●Binuswill charge each API call to the provided service
●API call pricing still need to be discussed on the next
meeting