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Accepted for/Published in: JMIR mHealth and uHealth

Date Submitted: Nov 11, 2019
Date Accepted: Jan 24, 2020

The final, peer-reviewed published version of this preprint can be found here:

Accurate Measurement of Handwash Quality Using Sensor Armbands: Instrument Validation Study

Wang C, Sarsenbayeva Z, Chen X, Dingler T, Goncalves J, Kostakos V

Accurate Measurement of Handwash Quality Using Sensor Armbands: Instrument Validation Study

JMIR Mhealth Uhealth 2020;8(3):e17001

DOI: 10.2196/17001

PMID: 32213469

PMCID: 7146248

Accurate measurement of hand-wash quality using sensor armbands: Instrument validation study

  • Chaofan Wang; 
  • Zhanna Sarsenbayeva; 
  • Xiuge Chen; 
  • Tilman Dingler; 
  • Jorge Goncalves; 
  • Vassilis Kostakos

ABSTRACT

Background:

Hand hygiene is a crucial and cost-effective method to prevent healthcare-associated infections, and in 2009 the World Health Organization (WHO) issued guidelines to encourage and standardize hand hygiene procedures. However, a common challenge in healthcare settings is low adherence, leading to low handwashing quality. Recent advances in machine learning and wearable sensing have made it possible to accurately quantify handwashing quality for the purpose of training, feedback, or accreditation.

Objective:

We measure the accuracy of a sensor armband (Myo armband) in detecting the steps and duration of the WHO procedures for handwashing and handrubbing.

Methods:

We recruited 20 participants (10 females; mean age 26.5 (SD = 3.3) years). In a semi-structured environment, we collect armband data (acceleration, gyroscope, orientation, and surface electromyography data) and video data from each participant during 15 handrub and 15 handwash sessions. We evaluate the detection accuracy for different armband placements, sensor configurations, user-dependent vs. independent models, and the use of bootstrapping.

Results:

Using a single armband the accuracy is 96% (SD = 0.01) for the user-dependent model, and 82% (SD = 0.08) for the user-independent model. This increases when using two armbands to 97% (SD = 0.01) and 91% (SD = 0.04) respectively. Performance increases when the armband is placed on the forearm (user-dependent: 97% (SD = 0.01); user-independent: 91% (SD = 0.04)) and decreases when placed on the arm (user-dependent: 96% (SD = 0.01); user-independent: 80% (SD = 0.06)). In terms of bootstrapping, user-dependent models can achieve more than 80% accuracy after 6 training sessions, and 90% with 16 sessions. Finally, we find that the combination of accelerometer and gyroscope minimize power consumption and cost while maximizing performance.

Conclusions:

A sensor armband can be used to measure relatively accurately hand hygiene quality, both in terms of handwashing and handrubbing. The performance is acceptable using a single armband worn in the upper arm, but can substantially improve by placing the armband in the forearm or by using two armbands.


 Citation

Please cite as:

Wang C, Sarsenbayeva Z, Chen X, Dingler T, Goncalves J, Kostakos V

Accurate Measurement of Handwash Quality Using Sensor Armbands: Instrument Validation Study

JMIR Mhealth Uhealth 2020;8(3):e17001

DOI: 10.2196/17001

PMID: 32213469

PMCID: 7146248

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