Capturing surgical images can be challenging. Issues include Health Insurance
Portability and Accountability Act (HIPAA) compliance, the sterile field and
interruptions in workflow.[1] Current technology is limited to handheld digital cameras (DCs) operated by
persons outside the sterile field or cameras mounted to the surgeons’ heads.
Adjusting camera options such as the field of view, lighting and timing while
limiting disruption of the operation can be difficult.The Google Glass™ heads-up-display system has been tested by the medical field for
applications such as image capture, live streaming and decision support.
Specifically, its hands-free voice control operating system is appealing to
surgeons. However, very few studies have been reported in the literature using
Google Glass™ for this purpose.[1-7] Common concerns about its use by
physicians include privacy with cloud data transmission, accuracy of data sent and
received and its clinical efficiency.This prospective pilot study evaluated the intraoperative and clinic workflow
efficiency of a proprietary application written for Google Glass™ to capture images
of the surgical field. The application links to the patient’s electronic medical
record (EMR) and transmits the captured images directly to their record. The study
compared this application to another proprietary application for image capture using
a cellular phone and to a handheld DC. The study was classified as a quality
improvement project with an institutional review board (IRB) exemption as the data
and images were de-identified and no patient care interventions were made. In
addition, surgical consent forms include permission to use captured images for
research and education at our institution.
Methods
Google Glass™ is a monocular heads-up-display unit that presents graphical
information to the upper outer corner of the peripheral vision of the user’s right
eye (Figure 1). The glasses
include a 5-megapixel camera, a microphone and speakers using bone conduction
technology. Its battery is embedded within the frame while supplemental power and
peripherals are connected via a standard micro USB port. Users interact with the
glasses using Google™ voice recognition and a touchpad on the right temple frame.
Google Glass™ runs on the Android operating system and includes support for Wi-Fi.[8]
Figure 1.
Google Glass™ Explorer Edition used in this study personally owned by lead
author.
Average setup times were 2.11 s, 9.91 s and 18.39 s for DC, IC and SV, respectively.
These times were equivalent between clinic and operating room settings as both were
performed before the patient encounter; that is, not scrubbed into the sterile
field. Ten patients were studied, four in the operating room and six in the wound
clinic (Table 1).
Table 1.
Comparative timing metrics for each modality and location.
Setup time: Logging in to the application (after phone and Glass™ turned
on) or turning on the digital camera. Patient selection time: Selecting
the correct patient within the application or capturing their name tag
ID number with the digital camera. Photo shooting time: Setting up the
shot including positioning, framing and capturing. Upload time: Time
from capture to upload to the EMR multimedia manager.
The average times to select the correct patient were 3.06 s, 14.77 s and 4.45 s
for SV, IC and DC, respectively (Table 1). Average image capture times
were very similar across platforms at 8.67 s, 7.77 s and 7.60 s for SV, IC and
DC, respectively. These were also the times taken to capture the initial patient
image with each modality. Alternatively, it took only an average of 4.9 s over
10 independent attempts to capture an image with SV by simply verbalizing the
image capture command without loading the viewfinder first. This was done with
the SV for subsequent images captured during the case. Significant differences
were noted, however in image upload times. While images captured by SV and IC
were instantaneously uploaded to the EMR’s multimedia manager, the DC images
took on average 1522 s to be manually uploaded to the patient’s records. This
was very user dependent. There were instances early in our study when the Google
Glasses™ powered down during a case due to battery power loss. Battery life was
not recorded in this study, but one 3- to 4-h case would exhaust the available
battery power. This was remedied by a wired supplemental battery pack worn in
the surgeon’s back pocket as well as software modifications allowing the SV
application to sleep, thereby conserving battery power draw from the screen.
Rarely, prolonged sleep time allowed the application to close during a case
which unfortunately rendered the glasses unusable without physically removing
them and logging in again. This was not possible without scrubbing out of the
case.
Outpatient surgical wound clinic
In the wound clinic, the average times to select the correct patient were 16.29
s, 7.35 s and 4.63 s for SV, IC and DC, respectively (Table 1). Image capture times were
again similar at 9.55 s, 5.28 s and 3.47 s, respectively. Once again SV capture
times included verbally calling up the viewfinder to line up the shot and
capture the image. As noted in the section “Operating room”, it took only an
average of 4.9 s to capture images with SV without loading the viewfinder first.
Upload times were significantly different with the DC taking on average 27,758 s
to upload to the patient’s multimedia manager. This was also user dependent.
Battery life was not a problem in the clinic setting as the glasses were removed
and connected to the micro USB charger in between cases. The SV application did
stay open in between most cases; however, prolonged downtime or sleep time did
occasionally require reopening the application and logging in with the user’s
credentials.
Usability surveys
Two usability surveys were taken from surgical residents that used SV in the
operating room for several cases (Table 2). There was very close
reliability in SUS scores between them. Both users found the system
well-integrated and easy to use and felt confident using it. They also found the
learning curve to be shallow without unnecessary complexity and felt that most
would learn the system quickly. Finally, they both would use the SV system
frequently. Separate comments by the users focused on the SV log in procedure
which required a keyboard and Bluetooth dongle. Suggestions included scanning a
QR code with the glasses versus a near-field communication (NFC) solution. They
also noted the inability to log back into the SV application while scrubbed
using the keyboard. Both users emphasized the need for initial hands-on
instruction by an experienced user. These users and the lead author (S.A.) were
impressed by the accuracy of the voice recognition by Google Glass™. Ambient
chatter was occasionally perceived as commands by the glasses while the user was
speaking to it.
Our prospective study quantified the workflow efficiency of a proprietary
HIPAA-compliant image capture application for Google Glass™. It is one of the very
few studies to compare the application’s performance on Google Glass™ with
traditional tools such as the DC and the handheld phone using standard metrics. SV’s
performance was comparable to that of IC with the added benefit of hands-free
intraoperative use by the surgeon through their point-of-view. Both SV and IC had
clear advantages over DC in terms of workflow efficiency when measured by
availability on the multimedia manager. The SV application was a prototype and
suffered some glitches that were not completely unexpected. These include logging
out during a longer case and occasional application crashes and forced shutdown.
Most glitches, however, were easily repaired with software updates. Many of the
difficulties with SV were in fact due to the hardware of Google Glass™ itself. This
included the user log on procedure which required a wireless keyboard dongle and
rendered the application and glasses nonfunctional in the unexpected event of
intraoperative application shutdown or logging off. Another difficulty was speaking
commands to the application in the operating room while others were also speaking.
The user could also not control the image size or zoom without moving closer or
farther away from the subject. This was possible in the outpatient clinic setting,
but difficult in a sterile operative field.Future work using Google Glass™ and the SV application would benefit from hardware
and firmware upgrades to the camera, battery and wireless input to include voice and
keyboards. The camera could also benefit from zoom and high dynamic range (HDR)
features which would enhance intraoperative images. The SV application could evolve
to include video capture, voice or text annotations and secure live streaming of
procedures. The latest iteration of Google Glass™ is currently being tested in
several industries including manufacturing and medicine.
Limitations
Our prospective study was only a pilot with a very small sample size of both users
and patients. We did not qualify differences in image quality or detail. The patient
selection was random depending on their availability in the clinic and operating
room. Standardized patient scenarios would help in comparing image quality in the
future. Our usability data was limited to S.A. and two residents.
Conclusion
SV performed equivalently with IC while DC took much longer to upload. Users found
the application easy to learn and use with some technical concerns about the
glasses. These included the log on procedure, ambient distraction of voice
recognition, viewfinder perspective and battery life. This was a successful pilot
study of a proprietary image capture application for Google Glass™ with quantified
comparative metrics not before published in the literature. Hardware limitations
with Google Glass™ did limit its effectiveness. Usability surveys of the SV
application on Google Glass™ were positive. Further research is warranted.
Authors: Oliver J Muensterer; Martin Lacher; Christoph Zoeller; Matthew Bronstein; Joachim Kübler Journal: Int J Surg Date: 2014-02-15 Impact factor: 6.071
Authors: Urs-Vito Albrecht; Ute von Jan; Joachim Kuebler; Christoph Zoeller; Martin Lacher; Oliver J Muensterer; Max Ettinger; Michael Klintschar; Lars Hagemeier Journal: J Med Internet Res Date: 2014-02-12 Impact factor: 5.428