A Comparison of Four Sensor-based Input Methods for Scanning Keyboards

Four sensor-based methods for computer input were compared. The methods were button, accelerometer, flex sensor, and pressure sensor. The sensors were held in the user's hand in a grip position (button, pressure) or attached via a Velcro band either to the index finger (flex) or on the back of the hand (accelerometer). The methods were used for the select operation with a single-switch scanning keyboard using a Qwerty letter arrangement. The setup used a 700 ms scanning interval, a 200 ms scanning delay (after each selection), and auditory feedback for switch activations. Twelve participants completed five text-entry tasks with each sensor. The text entry rates were slow, but in the expected range for single-switch input. Button selection was the fastest at 2.35 words per minute (wpm) and had the highest efficiency with 82%. The flex sensor followed at 2.26 wpm with 77% efficiency, followed by the pressure sensor at 2.07 wpm with 74% efficiency. The accelerometer was the slowest at 1.89 wpm and had the lowest efficiency at 68%. Statistical tests indicated a significant effect of sensor type on entry speed and efficiency, though post hoc comparisons revealed no pairwise significance, potentially due to the limited sample size. Qualitative results supported the findings: The button sensor received the most favourable user ratings across comfort, fatigue, and preference, with six of twelve participants selecting it as their preferred choice. Four participants selected the flex sensor as their preferred choice

Authors

Publication Details

Journal
AHFE international
Published
2025-01-01
DOI
https://doi.org/10.54941/ahfe1006730
Primary Topic
Tactile and Sensory Interactions
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Comparison of Four Sensor-based Input Methods for Scanning Keyboards

Sanjeet Kumar Patel, H. Liu, Katta Ramesh, Ajay Kumar Verma et al.
AHFE international
Tactile and Sensory Interactions
article

A Comparison of Four Sensor-based Input Methods for Scanning Keyboards

Sanjeet Kumar Patel, H. Liu, Katta Ramesh, Ajay Kumar Verma, Scott Mackenzie
article en

Abstract

Four sensor-based methods for computer input were compared. The methods were button, accelerometer, flex sensor, and pressure sensor. The sensors were held in the user's hand in a grip position (button, pressure) or attached via a Velcro band either to the index finger (flex) or on the back of the hand (accelerometer). The methods were used for the select operation with a single-switch scanning keyboard using a Qwerty letter arrangement. The setup used a 700 ms scanning interval, a 200 ms scanning delay (after each selection), and auditory feedback for switch activations. Twelve participants completed five text-entry tasks with each sensor. The text entry rates were slow, but in the expected range for single-switch input. Button selection was the fastest at 2.35 words per minute (wpm) and had the highest efficiency with 82%. The flex sensor followed at 2.26 wpm with 77% efficiency, followed by the pressure sensor at 2.07 wpm with 74% efficiency. The accelerometer was the slowest at 1.89 wpm and had the lowest efficiency at 68%. Statistical tests indicated a significant effect of sensor type on entry speed and efficiency, though post hoc comparisons revealed no pairwise significance, potentially due to the limited sample size. Qualitative results supported the findings: The button sensor received the most favourable user ratings across comfort, fatigue, and preference, with six of twelve participants selecting it as their preferred choice. Four participants selected the flex sensor as their preferred choice

AHFE internationalVol. -5
Affordable and clean energy
Openalex Percentile: Top 85%
Tactile and Sensory Interactions
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

A Comparison of Four Sensor-based Input Methods for Scanning Keyboards — Sanjeet Kumar Patel, H. Liu, et al. · AHFE international (2025) | TGRS Research Map | TGRS