Step counting for slow and intermittent ambulation based on a smartwatch accelerometer

Author(s):  
VIncenzo Genovese ◽  
Andrea Mannini ◽  
Angelo Sabatini
Keyword(s):  
2012 ◽  
Vol 2 (4) ◽  
pp. 259-270 ◽  
Author(s):  
Ian Cleland ◽  
Chris D. Nugent ◽  
Dewar D. Finlay ◽  
William P. Burns ◽  
Jennifer Bougourd ◽  
...  

2016 ◽  
Vol 47 (7) ◽  
pp. 1303-1315 ◽  
Author(s):  
David R. Bassett ◽  
Lindsay P. Toth ◽  
Samuel R. LaMunion ◽  
Scott E. Crouter
Keyword(s):  

2017 ◽  
Vol 5 (6) ◽  
pp. e88 ◽  
Author(s):  
François Modave ◽  
Yi Guo ◽  
Jiang Bian ◽  
Matthew J Gurka ◽  
Alice Parish ◽  
...  

Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2438 ◽  
Author(s):  
Armelle M. Ngueleu ◽  
Andréanne K. Blanchette ◽  
Désirée Maltais ◽  
Hélène Moffet ◽  
Bradford J. McFadyen ◽  
...  

With the growing interest in daily activity monitoring, several insole designs have been developed to identify postures, detect activities, and count steps. However, the validity of these devices is not clearly established. The aim of this systematic review was to synthesize the available information on the criterion validity of instrumented insoles in detecting postures activities and steps. The literature search through six databases led to 33 articles that met inclusion criteria. These studies evaluated 17 different insole models and involved 290 participants from 16 to 75 years old. Criterion validity was assessed using six statistical indicators. For posture and activity recognition, accuracy varied from 75.0% to 100%, precision from 65.8% to 100%, specificity from 98.1% to 100%, sensitivity from 73.0% to 100%, and identification rate from 66.2% to 100%. For step counting, accuracies were very high (94.8% to 100%). Across studies, different postures and activities were assessed using different criterion validity indicators, leading to heterogeneous results. Instrumented insoles appeared to be highly accurate for steps counting. However, measurement properties were variable for posture and activity recognition. These findings call for a standardized methodology to investigate the measurement properties of such devices.


Spinal Cord ◽  
2019 ◽  
Vol 57 (7) ◽  
pp. 571-578
Author(s):  
Erin Albaum ◽  
Emily Quinn ◽  
Saba Sedaghatkish ◽  
Parminder Singh ◽  
Amber Watkins ◽  
...  
Keyword(s):  

2017 ◽  
Vol 17 (11) ◽  
pp. 3453-3460 ◽  
Author(s):  
Fuqiang Gu ◽  
Kourosh Khoshelham ◽  
Jianga Shang ◽  
Fangwen Yu ◽  
Zhuo Wei

2010 ◽  
Vol 3 ◽  
pp. MEI.S3748 ◽  
Author(s):  
Tom Mikael Ahola

The Nokia Wrist–Attached Sensor Platform (NWSP) was developed at the Nokia Research Center during the NUADU project to facilitate research and demonstrations of use cases of wearable wireless sensors. A wrist–worn pedometer application was implemented as one of the demonstrations of the capabilities of the platform. In this paper the step counting algorithm is described and the performance is evaluated. The application is targeted for running exercise. However, the detection of steps during walking is also discussed.


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