SwipeSense: Exploring the Feasibility of Back-of-Device Swipe Interaction Using Built-In IMU Sensors MHCI030

The growing dimensions of smartphones have intensified the challenges associated with screen reachability. Back-of-device (BoD) interaction expands the range of reachability and offers a promising solution to mitigate screen occlusion while enhancing one-handed interactions. However, much of the existing research relies on incorporating additional hardware components. In this paper, we present SwipeSense a technique for exploring the feasibility of directional swipe interactions on the back of devices, utilizing built-in inertial measurement unit (IMU) sensors and machine learning models. We conducted a user study with 12 participants who performed 9600 BoD swipes in 8 distinct directions while holding the device naturally. The results of our machine learning models indicate that various directional swipes on the back of the device can be accurately distinguished using only the built-in IMU sensors of the phone, achieving a range of model accuracy between 72% and 95%. Furthermore, we showcase potential applications for these gestures.

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Publication Details

Journal
Proceedings of the ACM on Human-Computer Interaction
Published
2025-09-09
DOI
https://doi.org/10.1145/3743734
Primary Topic
Interactive and Immersive Displays
Type
article
Field-Weighted Citation Impact
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article

SwipeSense: Exploring the Feasibility of Back-of-Device Swipe Interaction Using Built-In IMU Sensors MHCI030

Mariana Shimabukuro, Benedict Leung, Ali Neshati, Neel Jayesh Shah
Proceedings of the ACM on Human-Computer Interaction
Interactive and Immersive Displays
article

SwipeSense: Exploring the Feasibility of Back-of-Device Swipe Interaction Using Built-In IMU Sensors MHCI030

Mariana Shimabukuro, Benedict Leung, Ali Neshati, Neel Jayesh Shah
article en

Abstract

The growing dimensions of smartphones have intensified the challenges associated with screen reachability. Back-of-device (BoD) interaction expands the range of reachability and offers a promising solution to mitigate screen occlusion while enhancing one-handed interactions. However, much of the existing research relies on incorporating additional hardware components. In this paper, we present SwipeSense a technique for exploring the feasibility of directional swipe interactions on the back of devices, utilizing built-in inertial measurement unit (IMU) sensors and machine learning models. We conducted a user study with 12 participants who performed 9600 BoD swipes in 8 distinct directions while holding the device naturally. The results of our machine learning models indicate that various directional swipes on the back of the device can be accurately distinguished using only the built-in IMU sensors of the phone, achieving a range of model accuracy between 72% and 95%. Furthermore, we showcase potential applications for these gestures.

Proceedings of the ACM on Human-Computer InteractionVol. 9(5)
Ontario Tech University (CA), Abiola Ajimobi Technical University Ibadan (NG)
Openalex Percentile: Top 76%
Interactive and Immersive Displays
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SwipeSense: Exploring the Feasibility of Back-of-Device Swipe Interaction Using Built-In IMU Sensors MHCI030 — Mariana Shimabukuro, Benedict Leung, et al. · Proceedings of the ACM on Human-Computer Interaction (2025) | TGRS Research Map | TGRS