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Rehabilitation Technology in Neurological PopulationsInhoud
1 Technology-based assessment and training for Parkinson Disease..................................................................................................3
1.1 Assessment of gait & balance in patients with PD using wearable technology.........................................................................3
1.2 Rehabilitation treatment with technology..................................................................................................................................7
1.3 Virtual reality and Parkinsons Disease........................................................................................................................................7
2 Technologically-supported upper limb rehabilitation.......................................................................................................................8
2.1 Mechanical Classification of devices...........................................................................................................................................8
2.2 Illustration of common devices, clinical evidence....................................................................................................................10
2.2.1 Robots................................................................................................................................................................................10
2.2.2 Non-actuator devices (Electromechanical devices)...........................................................................................................12
2.2.3 Sensors...............................................................................................................................................................................13
2.3 Classification of device by training modalities..........................................................................................................................13
2.4 Reflections on functional effects...............................................................................................................................................14
2.5 Sensors & developments including objects manipulation........................................................................................................15
2.5.1 Movement measurement (body or objects) in relation to virtual environments.............................................................15
2.5.2 Object manipulation...........................................................................................................................................................16
2.6 Take home messages................................................................................................................................................................16
3 Motor learning in the context of technology supported rehabilitation..........................................................................................16
3.1 Technology in rehabilitation: what, why, how?........................................................................................................................16
3.1.1 Motor learning...................................................................................................................................................................19
3.2 To which extent can technology be of additional value for motor learning?..........................................................................20
3.3 Possible pittfalls for technology use in rehabilitation?.............................................................................................................20
3.4 Take home messages................................................................................................................................................................21
4 Music technology in neuro rehab....................................................................................................................................................22
4.1 Gebruikswijze............................................................................................................................................................................22
4.1.1 Twee principes...................................................................................................................................................................22
4.2 In de praktijk..............................................................................................................................................................................23
4.2.1 Gangpatroon......................................................................................................................................................................23
4.2.2 Dynamische balans.............................................................................................................................................................24
4.2.3 Upper limb..........................................................................................................................................................................24
5 mHealth in telerehabilitation...........................................................................................................................................................26
5.1 Definities...................................................................................................................................................................................26
5.2 Technologie en ontwikkeling....................................................................................................................................................26
5.3 Clinical applications...................................................................................................................................................................27
5.3.1 mHealth in revalidatie........................................................................................................................................................27
5.3.2 mHealth in assessment......................................................................................................................................................27
5.4 Challenges en limieten..............................................................................................................................................................28
5.5 Conclusies..................................................................................................................................................................................29
,6 Bodyweight supported, robotic and VR applications during gait rehabilitation.............................................................................29
6.1 Bodyweight support systems....................................................................................................................................................29
6.2 Robotics.....................................................................................................................................................................................30
6.3 Patientencasus..........................................................................................................................................................................33
6.4 Virtual reality applications........................................................................................................................................................35
6.4.1 Applications........................................................................................................................................................................35
6.4.2 Effectiviteit.........................................................................................................................................................................35
6.4.3 Take home messages.........................................................................................................................................................38
6.5 Demo-session............................................................................................................................................................................38
6.5.1 VR for gait training.............................................................................................................................................................38
6.5.2 VR for neglect training.......................................................................................................................................................38
7 Revalidatietechnologie in Revarte – SWOT analyses.......................................................................................................................39
7.1 TECNOBODY..............................................................................................................................................................................39
7.2 SILVERFIT...................................................................................................................................................................................40
7.3 CMILL.........................................................................................................................................................................................41
7.4 EKSO GT.....................................................................................................................................................................................42
7.5 NEUROCOM BALANCE MASTER................................................................................................................................................43
,1 TECHNOLOGY-BASED ASSESSMENT AND TRAINING FOR PARKINSON DISEASE
1.1 ASSESSMENT OF GAIT & BALANCE IN PATIENTS WITH PD USING WEARABLE TECHNOLOGY
Capaciteit vs Performance
Supervised lab- of thuistest Tijdens ADL uitvoering zonder supervisie
Technologie brengt beiden dichter samen
PD patienten scoren hier beter in want focussen zich Itt andere pathologieën, waarbij het vertrouwen van ADL
meer op de taak en mindere stress zorgt voor een betere uitkomst, scoren
PD patienten hier minder op.
Inertial Measurement Unit (IMU)
Vroege validatie bestaat uit het bepalen van de accuraatheid, de mid-stage validatie focust zich meer op de klinische
efficacy. Doorheen het proces van in-labo protocol naar een thuis en een free living protocol wordt er gewerkt naar
een meest minimalistisch gevalideerd model.
Digital Outcome Measure (DMO) beschrijft een bredere term waar de IMU’s onder vallen. IMU’s zijn de meest
gebruikte draagbare sensoren voor gang en posturale instabiliteit bij PD patiënten in onderzoekssettings.
De metingen gebeuren in 3 assen en kunnen geconnecteerd worden via bluetooth
- Gyroscoop meet de positie tegenover de zwaartekracht
- Magnetometer meet de positie tegenover het magnetisch velden, dus de plaats in de ruimte
- Accelerometer meet versnellingen
Axivity -> activiteitmonitoring met 1 sensor ter hoogte van de lage rug gedurende 7 dagen aan een stuk.
DMO’s in Parkinson
= progressieve neurodegeneratieve aandoening met effect
op de basale ganglia (vnl de substantia nigra) waardoor er
verlies optreed van de dopamine neurotransmitters.
= leerstoornis met retentie en transfer deficits.
Bij Parkinson treed er een de-automatisatie op met een
verlies van motor vigour (motorische kracht) waardoor er
zich een verhoogde werking van compensatoire netwerken
voordoet. -> verhoogde cerebellaire werking + hogere
samensmelting van cognitieve, sensorisch en motorische
werking dan bij gezonder ouderen.
DMO’s
- ⇡ spontaan automatisch gedrag en ⇣ white coat effect
- kunnen beweging en exercise stimuleren
- kunnen leerretentie en transfers naar andere setting verbeteren
Fysieke activiteit -> discrepanties binnen self-reported en objectief gemeten physical activity en exercise -> DMO’s
tonen ons dat PD patiënten gemiddeld 30% minder actief zijn dan gezonden waarbij 1 op 6 > 7000 stappen haalt.
Pathologie-specifieke evidentie
Scoping review: in PD worden de meeste DMO- validiteitsstudies uitgevoerd, gevolgd door de MS populatie. Bij PD
en MS patiënten gebeuren de meeste metingen in een labo omdat hier gait kwaliteit belangrijk is. Bij COPD ziet men
voornamelijk thuismetingen omdat hier de gait kwantiteit belangrijker is.
DMO’s/IMU’s zijn seemingly objectieve metingen -> afhankelijk van locatie, gebruiksduur, outcome measures, etc.
, Free- living validatie = moeilijkste
Responsiveness -> twijfel over responsive outcomes die rehab effecten werkelijk weergeven
In de validatie pijplijn
Discriminatieve validiteit -> COPD focust zicht voornamelijk op volume terwijl bij PD gefocused wordt op pace en
variabliteit (speed en stride length)
APDM (naam bedrijf) – opal system -> 5 IMU’s gebruikt thv armen, benen en de romp -> meest gebruiksvriendelijke
en klinisch gevalideerde systeem
Combined protocol – IstandWalk
34 verschillende outcome parameters gemeten, verdeeld over de 4 verschillende stappen van het protocol. PD
patiënten ondervinden het meeste dysbalans en freezing bij de laatste stap Turning.
Gait outcome measures gemeten in een gait cycle van een pD patient niet altijd reliable <-> flat fooded PD gait ->
algoritme van de gait cycle segmentatie moet aangepast/ anders gevalideerd worden.
Frequency based measures -> intensity, smoothness, regularity
Power density spectrum analysis = meting van het signal
power spectrum tegenover de frequentie
Bij PD als de:
- dominante frequentie ⇣ dan ⇡ de stride time
- breedte van de dominante freq ⇡ dan ⇡ de variabiliteit
- amplitude ⇣ dan ⇣ de energie
Posturale stabiliteit outcomes -> postural sway metrics = dispersion area en frequency
Bij levodopagebruikers meer sway, minder posturale controle
Sway jerk = smoothness van posturale sway -> ⇡ sway = ⇣ posturale balans = ⇡ jerk
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