Poster presentation in International Stroke Conference 2018 of American Heart Association, January 2018. Authors: Petra Ijäs, Laura Mäkitie, Satu Kivelä, Taina Wahlman-Muranen, and Nina Forss from Department of Neurology, Helsinki University Hospital, Helsinki, Finland Niko Kiukkonen, Petri Selonen, Vlad Stirbu, Antero Taivalsaari, Lea Myyryläinen, Oskari Koskimies, and Mauri Honkanen from Nokia Technologies, Finland

1. REMOTE HOME MONITORING OF RISK FACTORS AFTER STROKE AND Ijäs P1, Mäkitie L1, Kivelä S1, Wahlman-Muranen T1, Kiukkonen,
N2, Selonen P2, Stirbu V2, Taivalsaari A2, Myyryläinen L2,
Koskimies O2, Honkanen M2, Forss N1.
1. Department of Neurology, Helsinki University Hospital,
Helsinki, Finland
2. Nokia Technologies, Finland
Up to 90% of strokes could be prevented by effective treatment
of the risk factors. However, there are major problems with the
implementation of prevention due to
• the low adherence of patients to medication and lifestyle
changes,
• patients are not reaching treatment targets, e.g. only 40% of
patients taking medication have blood pressure (BP) at
treatment goals,
• difficulties in the detection of risk factors, such as paroxysmal
atrial fibrillation (AF).
Thus new strategies are needed to improve secondary
prevention of chronic diseases like stroke.
BACKGROUND RESULTS
• Twenty-nine (97%) patients completed the study. One patient
discontinued due to unrelated serious illness.
• BP medication needed adjustment in 13 patients (43.3%)(Table 1).
• New AF was detected in 3 patients (10.3%)(Table 1). The mean
ECG monitoring time was 12.2 ± 7.6 days.
• Patients appraised that the home monitoring system was easy to
use (score 8.6/10) and most would recommend it to peers (score
8.9/10).
• No serious technical problems were encountered
TIA TO IMPROVE SECONDARY PREVENTION – A PILOT STUDY
• Remote home monitoring of risk factors after stroke is feasible.
• It may be an efficient way to improve secondary prevention by
uncovering unidentified risk factors and improving reaching of
treatment targets.
• Patients felt they understood their illness and risk factors better
and also felt more secured when home-monitored.
• Remote home monitoring is a promising tool for stroke
management.
Table 1. Patient characteristics and results
CONCLUSIONS
PATIENTS
• 30 patients (mean age 56.5 ± 11.6, 63% males) were
recruited: 16 had a minor stroke, 13 TIA or amaurosis fugax
and one a retinal infarction (Patient characteristics in Table 1).
• A remote home monitoring system was given at discharge
• Follow-up contacts: call by a stroke nurse at two weeks and a
physician’s end visit at three months.
• Additional contact if AF was detected or BP required
medication adjustment (Study protocol in Figure 1).
• Home remote monitoring was offered in addition to the normal
standard of care.
Variable At the
start
At 3
months
Sex (% males) 19 (63.3)
Age 56.5 ± 11.6
Smoking (current/former) 11 (36.6)
Hypertension 17 (56.7)
Dyslipidemia 24 (80.0)
Diabetes type I/II 7 (23.3)
Cardiac disease/risk factor 6 (23.3)
Index symptom
Stroke 16 (53.3)
TIA or amaurosis fugax 13 (43.3)
Retinal infarct 1 (3.3)
TOAST (stroke patients)
Large vessel stroke 1 (3.3)
Cardioembolic 2 (6.7)
Small vessel disease 2 (6.7)
Non-determined 13 (43.3)
Medication
Antihypertensive 16 (53.3) 23 (76.7)
Lipid 5 (16.7) 26 (86.7)
Antithrombotic 2 (6.7) 24 (80.0)
Anticoagulation 1 (3.3) 7 (23.3)
Adherence
All measurements 27 (90.0)
Suspension 1 (3.3)
Change in antihypertensive 13 (43.3)
Start 2 (6.7)
Increase in dose 9 (30.0)
Lowering of dose 3 (10.0)
EKG monitoring time 12.2 (±7.4)
(±7.4)
New-onset atrial fibrillation 3 (10.3)
DepartmentofNeurology
P.O.Box340
FIN-00029HUS
Finland
CORRESPONDENCE
PetraIjäs
MD,PhD,Adj.Professor
Neurologist
petra.ijas@hus.fi
NinaForss
MD,PhD,Professor
HeadofDepartment
nina.forss@hus.fi
• The system (Figure 2) comprised of a cloud backend for data
storage and processing, patient user interface (PUI; Figure 3),
and wireless BP meter and light-weight ECG device with
secured connection to clinician UI (CUI; Figure 4). Through
CUI, BP and ECG could be followed real-time and
individualized alarm limits could be set. ECG was
automatically analyzed in the cloud backend to detect AF
(Figure 5).
• Patients were recruited and treated in HUS. The PUI and
cloud backend and analysis tools were developed by Nokia.
CUI was developed in collaboration with Nokia and HUS. The
BP meter was manufactured by Omron and ECG device
(eMotion Faros®) by Mega Electronics ltd. Both are CE/FDA
approved. The system was maintained by Nokia.
METHODS
HYPOTHESIS
• Remote home monitoring may lead to better control of risk
factors by increasing measurements and patient awareness
and uncovering undetected risk factors.
• This pilot study investigates the feasibility of home monitoring
of BP and ECG after minor stroke or TIA.
Figure 2. Remote Home Monitoring System
4G Data
Connection
Patient App &
Gateway in a
Smartphone
Bluetooth
ECG and Blood pressure
Data
Ingestion
Analytics
EHR
Data
Visualization
Sensor Devices
Patient – Care Team Interaction
Clinician
App
Gives
Figure 3. Patient User Interface
Instructions on
the use of the devices
Gives information
on the risk factors
Reminders of the care plan
with a modern chat UI