Balcon Marinoni 2

8/12/2019 Balcon Marinoni 2

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BALCON-HYCON2 WorkshopBelgrade 2-3 July 2013

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Real-Time Operating Systems

for eHealth Wearable Devices

Mauro Marinoni, Gianluca Franchino

and Giorgio ButtazzoReTiS Lab, TeCIP Institute

Scuola superiore SantAnna - Pisa


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Outline

Embedded systems in e-health

Evolution

Issues

Real-time Operating systems

Erika kernel

Contributions

Case studies

Telemonitoring

Telerehabilitation


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Scenario

Recent technological advances have enabled the

development of low-cost, miniature medical devices,

they improve the communication among patients,physicians, and other health care centers.

This solution presents a lot of advantages like: reduced hospitalization;

improved efficiency;

speed up the diagnosis of diseases;

detect critical health conditions.

cut total costs;


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Embedded systems in e-health

Embedded systems for medical use have caused deepchanges in medical practice:

Automate tasks in the hospital

Remote logging (e.g., Holter monitor)

Automatic remote acquisition

Tele-rehabilitation


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Data Trust

In remote logging, data are analyzed by the physicianBEFORE being added to the health record;

In remote acquisition, data are added to the healthrecord and LATERvalidated by some physician;

Data included in the health record MUSTbe reliable


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Multi-sensor platforms

In new generations of medical devices:

Data are acquires from multiple sensors;

Sensors are sampled with different periods;

Some sensors sharethe same bus;

Several configuration of sensors and sample timescould be available.

THEN

Concurrency among tasks

Resource management


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Rehabilitation Tele-rehabilitation is characterized by an extra set of

constraints correlated with the feedback that must beprovided to both the remote supervisor and the patient.

To provide a responsive and natural experienceresponse times and jitters must be strictly bounded.

THEN

Temporal isolation reduce interference;

Real-time protocols reduce jitter;

Adaptive scheduling increases flexibility.


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E-health embedded devices

Summarizing the requirements:

Reliable chain of data from sensor to destination;

Multitasking and temporal isolation;

Resource management;

Adaptive scheduling;

Real-time communication.

Together with:

Maximize the lifetime.

Reduce development and certification costs;

Real-Time System


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Erika Enterprise

The proposed solution is based on the tiny real-timeoperating system Erika Enterprise:

Minimal kernel (few Kb footprint) for single and multicore

platforms.

Free, open-source and compliant with the OSEK/VDX APIwith an OSEK OIL compiler integrated into Eclipse.

Support for different architectures (8, 16 and 32 bits), hidinghardware complexity.

Interchangeable scheduling algorithms such as Fixed Prioritywith preemption thresholds, Stack Resource Policy (SRP),and Earliest Deadline First (EDF).

Support for automatic code generation from ScicosLab.
http://www.evidence.eu.com/


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ReTiS contributions

Real-time scheduling

aperiodic servers, resource reservation, shared resources

Resource management

overload handling, elastic tasks, adaptive allocation policies

Real-time communication

multi-hop communication, bandwidth allocation, task andpacket co-scheduling

Power management with timing constraintssupport for multiple algorithms for CPU and devices,integration of DVFS and DPM mechanisms


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Power management issues Power Management for Real-Time systems

Started focusing on CPU

Now technology allows more devices CPU is only partof the totalpower consumption

Embedded systems present strong interaction among each other and

with the environment

new constraints for energy-aware algorithms CMOS Power Dissipation due to:

Dynamic power consumption (switching activities)

Static power consumption (leakage current)

Energy Saving through:

Dynamic Voltage/Frequency Scaling (DVFS)

Dynamic Power Management (DPM)


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Power management issues (2)

In embedded real-time systems with energy

constraints, selecting the most appropriate energymanagement policy is not easy.

The result heavily depends on:

the platform characteristics (e.g., energy modesand profiles of the devices, frequency range andpower states of the CPU);

the application constraints (e.g., task deadlines,sensors acquisition delays, communicationbandwidth, etc.)


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Kernel support for power management

The Power Management is performed through a module in

the Real-Time OS The Scheduler selects

independently the tasks toexecute (FP or EDF)

The Power Manager choosesan appropriate runningconfiguration (i.e. speed andvoltage)

Although Applications and theScheduler can communicate

with Power Manager, they areindependent


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Kernel module architecture Power driver and Device driver abstract the device behavior using a

discrete set of states.

The Power Manager is divided in independent modules.

The API module implements the interfacedefined for the interaction with the kerneland Applications.

The CPU policy submodule implementsthe energy saving policies.

The CPU driver makes new configurationoperative.

Device policy implements the devicestrategies.

Device Interface offers a single accesspoint to the devices.


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Case Studies

Remote monitoring of physiological parameters

ASCOLTAproject

Kinematic tracking for telerehabilitation

Part of the WHITEJoint Open Lab


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ASCOLTA ProjectThis project has been funded by the Tuscany region to analyze

the possibility of remotely monitoring patientsrecovering from anheart failure.

The board allowsto acquire ECG,SPO2, breath rate,accelerometersand communicatestrough a WiFi link;


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ASCOLTA Project Information are stored in a server to be automatically

analyzed and accessed by physicians.

IMU d Ki ti


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IMU and Kinetics

Inertial Measurement Units (IMUs) are

becoming essential in monitoring the human body:

Games control

Wellness

Gait analysis

Patient monitoring

Rehabilitation

A. Hadjidja, M. Souila, A. Bouabdallaha, Y. Challala, H. Owenb,

Wireless sensor networks for rehabilitation applications: Challenges and

opportunities, Journal of Network and Computer Applications, 36(1), January 2013.

S G


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First case study: SisTAG

Wearable system for telemonitoring of the knee joint


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Current activity

Monitoring of joints using wireless inertial sensors.

Calculating angles

and measurementerrors

3D Avatar

Data filtering and

analysis

Recognition ofpostures andactions

N R l ti D


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Non Real-time Demo

Nodes Synchronization


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Nodes Synchronization

To compute node position and body postures it is

crucial that all data from nodes are acquired atthe same time instant;

Time information in embedded nodes could be

affected by jitters due to low quality clocksources;

Hence time synchronization

among nodes mustbe provided.

Integration with body kinematics


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BALCON-HYCON2 Workshop

Belgrade 2-3 July 2013

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Integration with body kinematics

Kinematic constraints of themonitored body can be used tocorrelate nodes positions;

Thus reducing local errorspresent in each single sensor(e.g., drift, random walk)


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Conclusions

E-health devices are more an more complex

everyday.

A real-time OS could provide:

multi-tasking support,

timing constraints guarantee,

HW abstraction to improve portability.

Two use cases have been shown to present theproposed approach.

Questions


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Questions


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thank you!

Mauro Marinoni - [email protected]

Giorgio Buttazzo - [email protected]

Gianluca Franchino - [email protected]

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Balcon Marinoni 2