Precise synchronization time stamp generation for Bluetooth low energy
Abstract
Nowadays wearable sensor devices are a growing industry field. Smart gadgets like fitness trackers monitor sport exercises and daily movements of the wearer. Sensor data is wirelessly transferred to smartphones and processed by sports and fitness apps. Depending on the application, a single sensor might not be sufficient. In ubiquitous computing, sport science and medicinal appliances, complex scenarios require multiple distributed sensors. However proper sensor data fusion is not possible without precise time synchronization among all units. The common wireless technology of wearables is Bluetooth Low Energy (BLE), which is integrated in every nowadays smartphone. But the architecture of BLE makes implementation of accurate time synchronization nearly impossible due to nondeterministic delays. In this paper we present two principles to obtain precise synchronization hardware time stamps, based on the power consumption of BLE System on Chips (SoC). Our concept exceeds the best-known accuracy for BLE and is more energy-efficient compared to related work. Using a common BLE SoC, we achieved a standard deviation of 0.9 microseconds.
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The prior method with the lowest average error of 9 ± 17 μs requires that custom hardware be added to the MCU system.
“The prior method, with the lowest average (±standard deviation) error of 9 ± 17 µs, requires that custom hardware be added to the MCU system [28].”
From Comparison between Two Time Synchronization and Data Alignment Methods for Multi-Channel Wearable Biosensor Systems Using BLE Protocol (2023) · cites this paper as [28]
An additional hardware approach provided time synchronization precision of 9 ± 17 μs.
“One such approach provided time synchronization precision of 9 ± 17 µs [28].”
From Comparison between Two Time Synchronization and Data Alignment Methods for Multi-Channel Wearable Biosensor Systems Using BLE Protocol (2023) · cites this paper as [28]
Researchers have used custom add-on hardware to detect a synchronizing signal.
“Alternatively, researchers have used custom add-on hardware to detect a synchronizing signal [28].”
From Comparison between Two Time Synchronization and Data Alignment Methods for Multi-Channel Wearable Biosensor Systems Using BLE Protocol (2023) · cites this paper as [28]
Cited by
Sorted by citations
Wang, H., Li, J., McDonald, B. E., Farrell, T. R., Huang, X., & Clancy, E. A. (2023) · Sensors · doi:10.3390/s23052465 · Cited by 18 · see citing works
- Authors
- Rheinlander, C. C., & Wehn, N.
- Affiliations
- University of Kaiserslautern (DE)
- ORCID
- Wehn, Norbert
- Venue
- 2016 IEEE SENSORS
- Publisher
- IEEE
- Published
- 2016-10
- Pages
- 1-3
- ISSN
- 1930-0395 (ISSN-L)
- OpenAlex
- W2575677173
- Cited by
- 24
- References
- 0
- Citations by year
- 2026: 2 · 2025: 2 · 2024: 3 · 2023: 3 · 2022: 6 · 2021: 4 · 2019: 1 · 2017: 3
- FWCI
- 1.14
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Proceedings of IEEE Sensors/Proceedings of IEEE Sensors ... (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › Bluetooth and Wireless Communication Technologies
- Physical Sciences › Computer Science › Computer Networks and Communications › Network Time Synchronization Technologies
- Social Sciences › Sociology and Political Science › Multimedia Communication and Technology
- Keywords
- Bluetooth Low Energy, clock synchronization, wearable sensors, sensor fusion, power consumption, system-on-chip, energy efficiency, distributed sensors, wireless sensor networks
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