Smartphone based Fuzzy Logic freezing of gait detection in Parkinson's Disease

Pepa, Lucia; Ciabattoni, Lucio; Verdini, Federica; Capecci, Marianna; Ceravolo, M.G.

doi:10.1109/mesa.2014.6935630

Cited by 42 publications

(26 citation statements)

References 25 publications

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“…have been successfully employed for system identification, control, and modeling in many areas [61,62]. The approach considered in this work is the linguistic fuzzy modeling (LFM) with Mamdani rule structure due to its capability to model human knowledge in an explicit way.…”

Section: Fuzzy Logic Approach Fuzzy Rule-based Systems (Frbs)mentioning

confidence: 99%

An Open and Modular Hardware Node for Wireless Sensor and Body Area Networks

et al. 2016

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Health monitoring is nowadays one of the hottest markets due to the increasing interest in prevention and treatment of physical problems. In this context the development of wearable, wireless, open-source, and nonintrusive sensing solutions is still an open problem. Indeed, most of the existing commercial architectures are closed and provide little flexibility. In this paper, an open hardware architecture for designing a modular wireless sensor node for health monitoring is proposed. By separating the connection and sensing functions in two separate boards, compliant with the IEEE1451 standard, we add plug and play capabilities to analog transducers, while granting at the same time a high level of customization. As an additional contribution of the work, we developed a cosimulation tool which simplifies the physical connection with the hardware devices and provides support for complex systems. Finally, a wireless body area network for fall detection and health monitoring, based on wireless node prototypes realized according to the proposed architecture, is presented as an application scenario.

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Section: Fuzzy Logic Approach Fuzzy Rule-based Systems (Frbs)mentioning

confidence: 99%

An Open and Modular Hardware Node for Wireless Sensor and Body Area Networks

et al. 2016

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“…Some studies, on the other hand, aimed to detect FoG, a common motor impairment to suffer an inability to walk in PD patients. Pepa et al [58] presented a smartphone-integrated accelerometer-based system to detect the FoG. They developed a linguistic fuzzy modelling (LFM) with Mamdani rule structure by fusing the information of freeze index, energy sum, cadency variation, and energy derivative ratio with a sensitivity of 89% and a specificity of 97%.…”

Section: Smartphone-based Solutionsmentioning

confidence: 99%

“…Given the relatively small number of classifier-based studies in this area and the wide variety of research questions addressed, ranging from activity classification to different symptom severity level assessment, it is currently difficult to address which classifier is ideal in PD populations for mHealth. Meanwhile, the accuracy levels of the classifiers were generalized on small sample sizes ranging from 5 to 27 subjects [50][51][52][53][55][56][57][58][59][60][61]. Only one out of these studies enlisted a relatively larger sample of 92 patients with PD and 81 controls [54].…”

Section: Limitations and Challengesmentioning

confidence: 99%

The Emerging Wearable Solutions in mHealth

Zhao¹,

Li²,

Tsien³

2016

Mobile Health Technologies - Theories and Applications

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The marriage of wearable sensors and smartphones have fashioned a foundation for mobile health technologies that enable healthcare to be unimpeded by geographical boundaries. Sweeping efforts are under way to develop a wide variety of smartphonelinked wearable biometric sensors and systems. This chapter reviews recent progress in the field of wearable technologies with a focus on key solutions for fall detection and prevention, Parkinson's disease assessment and cardiac disease, blood pressure and blood glucose management. In particular, the smartphone-based systems, without any external wearables, are summarized and discussed.

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“…Fuzzy rule-based systems (FRBS) have been successfully employed for system identification, control and modeling in many areas [9], [10], [11]. 1 depicts the block diagram and the variables involved in the whole comfort control process.…”

Section: Fuzzy Logic Algorithmmentioning

confidence: 99%

Humidex based multi room thermal comfort regulation via fuzzy logic

Ciabattoni

Cimini

Ferracuti

et al. 2015

2015 International Symposium on Consumer Electronics (ISCE)

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In this paper we introduce a novel approach for multi room comfort control based on humidex index. The aim of the system is to reach and maintain comfort conditions through a fuzzy logic controller. The control system has been experimentally tested in an apartment in the central east coast of Italy. Temperature regulation performances have been compared with those of a classical PID based thermostat.

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Smartphone based Fuzzy Logic freezing of gait detection in Parkinson's Disease

Cited by 42 publications

References 25 publications

An Open and Modular Hardware Node for Wireless Sensor and Body Area Networks

An Open and Modular Hardware Node for Wireless Sensor and Body Area Networks

The Emerging Wearable Solutions in mHealth

Humidex based multi room thermal comfort regulation via fuzzy logic

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