Abstract:
Afterq decadesq ofq evolution,q measuringq instrumentsq forq quantitativeq gaitq analysisq haveq
becomeq anq importantq clinicalq toolq forq assessingq pathologiesq manifestedq byq gaitq abnormalities.q
However,q suchq instrumentsq tendq toq beq expensiveq andq requireq expertq operationq andq maintenanceq
besidesq theirq highq cost,q thusq limitingq themq toq onlyq aq smallq numberq ofq specializedq centers.q Gaitq
analysisq inq mostq clinicsq todayq stillq reliesq onq observation-basedq assessment.q Recentq advancesq inq
wearableq sensors,q especiallyq inertialq bodyq sensors,q haveq openedq aq promisingq futureq forq gaitq
analysis.q Notq onlyq canq theseq sensorsq beq moreq easilyq adoptedq inq clinicalq diagnosisq andq treatmentq
proceduresq thanq theirq currentq counterparts,q butq theyq canq alsoq monitorq gaitq continuouslyq outsideq
clinics.
So, after completing our research about Gait analysis and wearable sensors. We designed
and assembled the hardware. Then we started getting values from sensors and build the algorithm
to calculate step count, step length and step frequency.
We are showing these values on mobile app and as well as storing them on cloud database
for analysis of progress. Physiotherapist will be able to analyze the progress and advice their
patients.
