Annals of Biomedical Engineering

, Volume 44, Issue 4, pp 1234–1245 | Cite as

In Vivo Evaluation of Wearable Head Impact Sensors

  • Lyndia C. Wu
  • Vaibhav Nangia
  • Kevin Bui
  • Bradley Hammoor
  • Mehmet Kurt
  • Fidel Hernandez
  • Calvin Kuo
  • David B. CamarilloEmail author


Inertial sensors are commonly used to measure human head motion. Some sensors have been tested with dummy or cadaver experiments with mixed results, and methods to evaluate sensors in vivo are lacking. Here we present an in vivo method using high speed video to test teeth-mounted (mouthguard), soft tissue-mounted (skin patch), and headgear-mounted (skull cap) sensors during 6–13 g sagittal soccer head impacts. Sensor coupling to the skull was quantified by displacement from an ear-canal reference. Mouthguard displacements were within video measurement error (<1 mm), while the skin patch and skull cap displaced up to 4 and 13 mm from the ear-canal reference, respectively. We used the mouthguard, which had the least displacement from skull, as the reference to assess 6-degree-of-freedom skin patch and skull cap measurements. Linear and rotational acceleration magnitudes were over-predicted by both the skin patch (with 120% NRMS error for \(a_{\rm mag}\), 290% for \(\alpha _{\rm mag}\)) and the skull cap (320% NRMS error for \(a_{\rm mag}\), 500% for \(\alpha _{\rm mag}\)). Such over-predictions were largely due to out-of-plane motion. To model sensor error, we found that in-plane skin patch linear acceleration in the anterior–posterior direction could be modeled by an underdamped viscoelastic system. In summary, the mouthguard showed tighter skull coupling than the other sensor mounting approaches. Furthermore, the in vivo methods presented are valuable for investigating skull acceleration sensor technologies.


Head impact sensors Traumatic brain injury Wearable sensors Instrumented mouthguard Instrumented skin patch Instrumented skull cap High speed video Soft tissue modeling 



We thank X2 Biosystems Inc. for supplying skin patch sensors. The study was supported by the National Institutes of Health (NIH) National Institute of Biomedical Imaging and Bioengineering (NIBIB) 3R21EB01761101S1, David and Lucile Packard Foundation 38454, and the Stanford Child Health Research Institute Transdisciplinary Initiatives Program.

Conflict of interest

The authors have no personal or financial conflicts of interest related to this study.

Supplementary material

10439_2015_1423_MOESM1_ESM.pdf (44 kb)
Supplementary material 1 (pdf 44 KB)
10439_2015_1423_MOESM2_ESM.pdf (69 kb)
Supplementary material 2 (pdf 69 KB)
10439_2015_1423_MOESM3_ESM.pdf (76 kb)
Supplementary material 3 (pdf 75 KB)


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Copyright information

© Biomedical Engineering Society 2015

Authors and Affiliations

  • Lyndia C. Wu
    • 1
  • Vaibhav Nangia
    • 2
  • Kevin Bui
    • 1
  • Bradley Hammoor
    • 1
  • Mehmet Kurt
    • 1
  • Fidel Hernandez
    • 2
  • Calvin Kuo
    • 2
  • David B. Camarillo
    • 1
    • 2
    Email author
  1. 1.Department of BioengineeringStanford UniversityStanfordUSA
  2. 2.Department of Mechanical EngineeringStanford UniversityStanfordUSA

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