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Inertial sensor-based step length estimation model by means of principal component analysis
ID
Vezočnik, Melanija
(
Avtor
),
ID
Kamnik, Roman
(
Avtor
),
ID
Jurič, Matjaž B.
(
Avtor
)
PDF - Predstavitvena datoteka,
prenos
(1,63 MB)
MD5: C0B07F1C1E1F1A6634F0987E8D6BD00D
URL - Izvorni URL, za dostop obiščite
https://www.mdpi.com/1424-8220/21/10/3527
Galerija slik
Izvleček
Inertial sensor-based step length estimation has become increasingly important with the emergence of pedestrian-dead-reckoning-based (PDR-based) indoor positioning. So far, many refined step length estimation models have been proposed to overcome the inaccuracy in estimating distance walked. Both the kinematics associated with the human body during walking and actual step lengths are rarely used in their derivation. Our paper presents a new step length estimation model that utilizes acceleration magnitude. To the best of our knowledge, we are the first to employ principal component analysis (PCA) to characterize the experimental data for the derivation of the model. These data were collected from anatomical landmarks on the human body during walking using a highly accurate optical measurement system. We evaluated the performance of the proposed model for four typical smartphone positions for long-term human walking and obtained promising results: the proposed model outperformed all acceleration-based models selected for the comparison producing an overall mean absolute stride length estimation error of 6.44 cm. The proposed model was also least affected by walking speed and smartphone position among acceleration-based models and is unaffected by smartphone orientation. Therefore, the proposed model can be used in the PDR-based indoor positioning with an important advantage that no special care regarding orientation is needed in attaching the smartphone to a particular body segment. All the sensory data acquired by smartphones that we utilized for evaluation are publicly available and include more than 10 h of walking measurements.
Jezik:
Angleški jezik
Ključne besede:
gait model
,
inertial sensors
,
open-source dataset
,
smartphone
,
step length estimation model
Vrsta gradiva:
Članek v reviji
Tipologija:
1.01 - Izvirni znanstveni članek
Organizacija:
FRI - Fakulteta za računalništvo in informatiko
FE - Fakulteta za elektrotehniko
Status publikacije:
Objavljeno
Različica publikacije:
Objavljena publikacija
Leto izida:
2021
Št. strani:
22 str.
Številčenje:
Vol. 21, iss. 10, art. 3527
PID:
20.500.12556/RUL-135443
UDK:
681.586:004.382.745
ISSN pri članku:
1424-8220
DOI:
10.3390/s21103527
COBISS.SI-ID:
64014851
Datum objave v RUL:
15.03.2022
Število ogledov:
726
Število prenosov:
137
Metapodatki:
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Objavi na:
Gradivo je del revije
Naslov:
Sensors
Skrajšan naslov:
Sensors
Založnik:
MDPI
ISSN:
1424-8220
COBISS.SI-ID:
10176278
Licence
Licenca:
CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
Povezava:
http://creativecommons.org/licenses/by/4.0/deed.sl
Opis:
To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.
Začetek licenciranja:
19.05.2021
Sekundarni jezik
Jezik:
Slovenski jezik
Ključne besede:
model hoje
,
inercijski senzorji
,
javna podatkovna množica
,
pametni telefon
,
model za oceno dolžine koraka
Projekti
Financer:
ARRS - Agencija za raziskovalno dejavnost Republike Slovenije
Številka projekta:
P2-0359
Naslov:
Vseprisotno računalništvo
Financer:
ARRS - Agencija za raziskovalno dejavnost Republike Slovenije
Številka projekta:
P2-0228
Naslov:
Analiza in sinteza gibanja pri človeku in stroju
Financer:
Drugi - Drug financer ali več financerjev
Program financ.:
University of Ljubljana
Številka projekta:
704-8/2016-330
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