A relaxation system adapting to user's condition-identification of relationship between massage intensity and heart rate variability

Hasegawa, Yasuhisa; Ootsuka, Takeo; Fukuda, Toshio; Arai, Fumihito; Kawaguchi, M.

doi:10.1109/robot.2001.933110

Cited by 8 publications

(2 citation statements)

References 7 publications

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“…The routine and the pressures derive from the physiotherapists’ experience and available sensory feedback from the MM routine or provided by the patient. The gestures of the physiotherapist cannot be anticipated by the person, thus resulting in a retroactive mode of action control with an ongoing central integration of proprioceptive feedback ( Hasegawa et al, 2001 ). Although the participant can adjust muscle tone at his convenience, he is primarily confronted with a retroactive mode of action control ( Braver, 2012 ).…”

Section: Manual Massage and Foam Rolling At The Scope Of Motor Contromentioning

confidence: 99%

Selective Effects of Manual Massage and Foam Rolling on Perceived Recovery and Performance: Current Knowledge and Future Directions Toward Robotic Massages

et al. 2020

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Manual massage and foam rolling are commonly used by athletes for warm-up and recovery, as well as by healthy individuals for well-being. Manual massage is an ancient practice requiring the intervention of an experienced physiotherapist, while foam rolling is a more recent self-administered technique. These two topics have been largely studied in isolation from each other. In the present review, we first provide a deep quantitative literature analysis to gather the beneficial effects of each technique through an integrative account, as well as their psychometric and neurophysiological evaluations. We then conceptually consider the motor control strategies induced by each type of massage. During manual massage, the person remains passive, lying on the massage table, and receives unanticipated manual pressure by the physiotherapist, hence resulting in a retroactive mode of action control with an ongoing central integration of proprioceptive feedback. In contrast, while performing foam rolling, the person directly exerts pressures through voluntary actions to manipulate the massaging tool, therefore through a predominant proactive mode of action control, where operations of forward and inverse modeling do not require sensory feedback. While these opposite modes of action do not seem to offer any compromise, we then discuss whether technological advances and collaborative robots might reconcile proactive and retroactive modes of action control during a massage, and offer new massage perspectives through a stochastic sensorimotor user experience. This transition faculty, from one mode of control to the other, might definitely represent an innovative conceptual approach in terms of human-machine interactions.

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Section: Manual Massage and Foam Rolling At The Scope Of Motor Contromentioning

confidence: 99%

Selective Effects of Manual Massage and Foam Rolling on Perceived Recovery and Performance: Current Knowledge and Future Directions Toward Robotic Massages

et al. 2020

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“…However, there are still some challenges such as the differences in individual physiological signals [18,19]. These differences exist not only between people, but also between individuals at different background levels, i.e., each humanoid has specific body conditions which cause diverse physiological signals.…”

Section: Introductionmentioning

confidence: 99%

A Transductive Model-based Stress Recognition Method Using Peripheral Physiological Signals

Xie

Wang

2019

Sensors

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Existing research on stress recognition focuses on the extraction of physiological features and uses a classifier that is based on global optimization. There are still challenges relating to the differences in individual physiological signals for stress recognition, including dispersed distribution and sample imbalance. In this work, we proposed a framework for real-time stress recognition using peripheral physiological signals, which aimed to reduce the errors caused by individual differences and to improve the regressive performance of stress recognition. The proposed framework was presented as a transductive model based on transductive learning, which considered local learning as a virtue of the neighborhood knowledge of training examples. The degree of dispersion of the continuous labels in the y space was also one of the influencing factors of the transductive model. For prediction, we selected the epsilon-support vector regression (e-SVR) to construct the transductive model. The non-linear real-time features were extracted using a combination of wavelet packet decomposition and bi-spectrum analysis. The performance of the proposed approach was evaluated using the DEAP dataset and Stroop training. The results indicated the effectiveness of the transductive model, which had a better prediction performance compared to traditional methods. Furthermore, the real-time interactive experiment was conducted in field studies to explore the usability of the proposed framework.

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Iterative learning control of shape memory alloy actuators with thermoelectric temperature regulation for a multifunctional car seat

Menon

Asada

2006

2006 American Control Conference

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A relaxation system adapting to user's condition-identification of relationship between massage intensity and heart rate variability

Cited by 8 publications

References 7 publications

Selective Effects of Manual Massage and Foam Rolling on Perceived Recovery and Performance: Current Knowledge and Future Directions Toward Robotic Massages

Selective Effects of Manual Massage and Foam Rolling on Perceived Recovery and Performance: Current Knowledge and Future Directions Toward Robotic Massages

A Transductive Model-based Stress Recognition Method Using Peripheral Physiological Signals

Iterative learning control of shape memory alloy actuators with thermoelectric temperature regulation for a multifunctional car seat

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