HandRate: Heart Rate Monitoring While Simply Holding a Smartphone

Jiokeng, Kevin; Jakllari, Gentian; Beylot, André‐Luc

doi:10.1109/percom50583.2021.9439134

Cited by 5 publications

(3 citation statements)

References 40 publications

(39 reference statements)

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“…Various devices, including wearables [6] and infrared cameras [7], have been used to monitor temperature changes and predict thermal preferences. Additional data like heartbeat rates [12], obtained via smartphones [14] and in-ear microphones [15], or physical activity levels, detected through wearables [16], [17], also contribute to understanding occupants' thermal sensations. The main applicability challenges for sensor-based systems are the costs associated with widespread deployment and encouraging users to share data from personal devices.…”

Section: Related Workmentioning

confidence: 99%

Co-zyBench: Using Co-Simulation and Digital Twins to Benchmark Thermal Comfort Provision in Smart Buildings

Ma,

Panic,

Yus

et al. 2024

2024 IEEE International Conference on Pervasive Computing and Communications (PerCom)

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Heating, Ventilation, and Air Conditioning (HVAC) systems account for 40% to 50% of energy usage in commercial buildings. Thus, innovative ways to control and manage HVAC systems while preserving occupants' comfort are required. Stateof-the-art solutions employ pervasive systems with sensors or smart devices to gauge individual thermal sensations, yet assessing these methods is challenging. Real-world experiments are expensive, limited in access, and often overlook occupant and regional diversity. To address this, we introduce Co-zyBench, a benchmark tool using a Digital Twin (DT) approach for evaluating personalized thermal comfort systems. It employs a co-simulation middleware interfacing between a DT of the smart building and its HVAC system and another DT representing occupants' dynamic thermal preferences in various spaces. The DTs that support Co-zyBench are generated based on information, including data captured by sensors, of the space in which the thermal comfort system has to be evaluated. Co-zyBench incorporates metrics for energy consumption, thermal comfort, and occupant equality. It also features reference DTs based on standard buildings, HVAC systems, and occupants with diverse thermal preferences.

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Section: Related Workmentioning

confidence: 99%

Co-zyBench: Using Co-Simulation and Digital Twins to Benchmark Thermal Comfort Provision in Smart Buildings

Ma,

Panic,

Yus

et al. 2024

2024 IEEE International Conference on Pervasive Computing and Communications (PerCom)

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“…While some studies have already explored HR estimation using different subject positions (e.g., standing and walking) and measuring locations (e.g., in the hand (32) and pants pocket (33)), these methods utilized either SCG signals (32,33) or MCG signals from non-smartphone sources. Given the potential of GCG signals, further investigation into GCG signal collection from various postures and sites for HR estimation is warranted.…”

Section: Exploring the Potential Of Smartphonebased Gcg For Heart Rat...mentioning

confidence: 99%

Revolutionizing smartphone gyrocardiography for heart rate monitoring: overcoming clinical validation hurdles

Elgendi,

Wu,

Guan

et al. 2023

Front. Cardiovasc. Med.

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Accurate heart rate (HR) measurement is crucial for optimal cardiac health, and while conventional methods such as electrocardiography and photoplethysmography are widely used for continuous daily monitoring, they may face practical limitations due to their dependence on external sensors and susceptibility to motion artifacts. In recent years, mechanocardiography (MCG)-based technologies, such as gyrocardiography (GCG) and seismocardiography (SCG), have emerged as promising alternatives to address these limitations. GCG has shown enhanced sensitivity and accuracy for HR detection compared to SCG, although its benefits are often overlooked in the context of the widespread use of accelerometers in HR monitoring applications. In this perspective, we aim to explore the potential and challenges of GCG, while recognizing that other technologies, including photoplethysmography and remote photoplethysmography, also have promising applications for HR monitoring. We propose a roadmap for future research to unlock the transformative capabilities of GCG for everyday heart rate monitoring.

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“…For instance, heart rate measurements can be easily collected by hand wrists and smart watches to diagnose sleep deprivation and stress [22,41]. Heart rate also has been estimated solely by grabbing a smartphones [26]. Respiratory information has been collected through the microphone of smartphones to diagnose respiratory diseases [20,21], e.g., COVID-19.…”

Section: Related Workmentioning

confidence: 99%

Hippo

Yin

Liyanage

Ottun

et al. 2022

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.

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Hand-grip strength is widely used to estimate muscle strength and it serves as a general indicator of the overall health of a person, particularly in aging adults. Hand-grip strength is typically estimated using dynamometers or specialized force resistant pressure sensors embedded onto objects. Both of these solutions require the user to interact with a dedicated measurement device which unnecessarily restricts the contexts where estimates are acquired. We contribute HIPPO, a novel non-intrusive and opportunistic method for estimating hand-grip strength from everyday interactions with objects. HIPPO re-purposes light sensors available in wearables (e.g., rings or gloves) to capture changes in light reflectivity when people interact with objects. This allows HIPPO to non-intrusively piggyback everyday interactions for health information without affecting the user's everyday routines. We present two prototypes integrating HIPPO, an early smart glove proof-of-concept, and a further optimized solution that uses sensors integrated onto a ring. We validate HIPPO through extensive experiments and compare HIPPO against three baselines, including a clinical dynamometer. Our results show that HIPPO operates robustly across a wide range of everyday objects, and participants. The force strength estimates correlate with estimates produced by pressure-based devices, and can also determine the correct hand grip strength category with up to 86% accuracy. Our findings also suggest that users prefer our approach to existing solutions as HIPPO blends the estimation with everyday interactions.

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HandRate: Heart Rate Monitoring While Simply Holding a Smartphone

Cited by 5 publications

References 40 publications

Co-zyBench: Using Co-Simulation and Digital Twins to Benchmark Thermal Comfort Provision in Smart Buildings

Co-zyBench: Using Co-Simulation and Digital Twins to Benchmark Thermal Comfort Provision in Smart Buildings

Revolutionizing smartphone gyrocardiography for heart rate monitoring: overcoming clinical validation hurdles

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