2022 IEEE International Workshop on Sport, Technology and Research (STAR) 2022
DOI: 10.1109/star53492.2022.9860001
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A wearable system for respiratory signal filtering based on activity: a preliminary validation

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Cited by 11 publications
(4 citation statements)
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“…The current work presents a new approach for the remote monitoring of respiratory kinematics via smartphone-embedded sensors. The state of the art already reports similar methodologies; however, most of them rely on the adoption of wireless communication with standalone transducers and wearable devices [26,27], or they are extremely focused on the estimation of RR only [28], without a deep investigation into the effect of different device positions on the chest-abdomen. In fact, although smartphone-embedded IMUs are adopted in a few cases for respiratory kinematics recording, they are used to monitor a limited set of positions, neglecting the chest-abdomen kinematic difference [28,29].…”
Section: Discussionmentioning
confidence: 99%
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“…The current work presents a new approach for the remote monitoring of respiratory kinematics via smartphone-embedded sensors. The state of the art already reports similar methodologies; however, most of them rely on the adoption of wireless communication with standalone transducers and wearable devices [26,27], or they are extremely focused on the estimation of RR only [28], without a deep investigation into the effect of different device positions on the chest-abdomen. In fact, although smartphone-embedded IMUs are adopted in a few cases for respiratory kinematics recording, they are used to monitor a limited set of positions, neglecting the chest-abdomen kinematic difference [28,29].…”
Section: Discussionmentioning
confidence: 99%
“…In the literature, accelerometer measurements for respiratory kinematics at the chest and abdomen level have already been reported [23][24][25], with successful results in different contexts. From the literature, it appears that mostly wearable systems with standalone sensors and wireless communication have been used [26,27], with few works proposing smartphones for respiratory rate monitoring [28,29]. Moreover, an overall kinematic evaluation correlated to the chest-abdominal device position has not been reported.…”
Section: Introductionmentioning
confidence: 99%
“…Preliminary validation data during dynamic activities (walking and running at different speeds) showed good agreement between the presented IMU-based system and a Cosmed K5 metabolic cart, as shown in a work by Angelucci et al . 7 In dynamic conditions, a fine-tuning of the algorithm by Cesareo et al . 17 to adapt the code to the processing of breathing during dynamic activities was added by including the knowledge of the performed activity in the respiratory signal processing.…”
Section: Methodsmentioning
confidence: 99%
“…Physiological measurements can consider a single parameter, for example, HR, peripheral blood oxygen saturation, respiratory rate [27], and skin temperature, or could be more complex measures combining data from several sensors, such as in the cases of sleep analysis, estimation of energy expenditure, and analysis of physiological parameters with respect to the activity [28]. Even pathophysiological conditions could be accurately detected after appropriate processing of the data, for instance, atrial fibrillation detection [29], high serum glucose level detection, and fall detection [30].…”
Section: Wearables-benefits and Current Limitationsmentioning
confidence: 99%