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Erschienen in:
Wearable and Wireless Systems for Gait Analysis and Reflex Quantification Kapitel lesen Erstes Kapitel lesen

2018 | OriginalPaper | Buchkapitel

7. Bluetooth Inertial Sensors for Gait and Reflex Response Quantification with Perspectives Regarding Cloud Computing and the Internet of Things

verfasst von : Robert LeMoyne, Timothy Mastroianni

Erschienen in: Wearable and Wireless Systems for Healthcare I

Verlag: Springer Singapore

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Abstract

Bluetooth wireless enables localized connectivity to a smartphone, portable media device, and tablet. Rather than using these devices as wearable and wireless systems alone, the nature of Bluetooth wireless enables locally situated inertial sensors to be mounted to a subject for quantified evaluation of gait. The smartphone, portable media device, and tablet can then wirelessly transmit the data to a Cloud Computing resource for post-processing. Preliminary demonstration is presented regarding the machine learning classification of gait for Friedreich’s ataxia. A perspective of the application of Bluetooth wireless for reflex quantification is presented. Themes, such as sensor fusion and the Internet of Things, are further discussed. The prevalence of Bluetooth wireless further establishes the realization of Network Centric Therapy.

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Vorheriges Kapitel Smartphones and Portable Media Devices as Wearable and Wireless Systems for Gait and Reflex Response Quantification
Nächstes Kapitel Quantifying the Spatial Position Representation of Gait Through Sensor Fusion
Literatur
1.
LeMoyne R, Coroian C, Cozza M, Opalinski P, Mastroianni T, Grundfest W (2009) The merits of artificial proprioception, with applications in biofeedback gait rehabilitation concepts and movement disorder characterization. Biomedical Engineering, 165–198
2.
LeMoyne R, Coroian C, Mastroianni T, Grundfest W (2008) Accelerometers for quantification of gait and movement disorders: a perspective review. J Mech Med Biol 8(02):137–152CrossRef
3.
LeMoyne R, Mastroianni T, Coroian C, Grundfest W (2011) Tendon reflex and strategies for quantification, with novel methods incorporating wireless accelerometer reflex quantification devices, a perspective review. J Mech Med Biol 11(03):471–513CrossRef
4.
LeMoyne RC (2010) Wireless quantified reflex device. PhD Dissertation UCLA
5.
LeMoyne R, Jafari R, Jea D (2005) Fully quantified evaluation of myotatic stretch reflex. In: 35th Society for Neuroscience Annual Meeting
6.
LeMoyne R, Dabiri F, Jafari R (2008) Quantified deep tendon reflex device, second generation. J Mech Med Bio 8(01):75–85CrossRef
7.
LeMoyne R, Coroian C, Mastroianni T, Grundfest W (2008) Quantified deep tendon reflex device for response and latency, third generation. J Mech Med Bio 8(04):491–506CrossRef
8.
LeMoyne R, Mastroianni T, Coroian C, Grundfest W (2010) Wireless three dimensional accelerometer reflex quantification device with artificial reflex system. J Mech Med Bio 10(03):401–415CrossRef
9.
LeMoyne R, Coroian C, Mastroianni T (2009) Evaluation of a wireless three dimensional MEMS accelerometer reflex quantification device using an artificial reflex system. In: ICME International Conference on IEEE, Complex Medical Engineering (CME), pp 1–5
10.
LeMoyne R, Coroian C, Mastroianni T (2009) Wireless accelerometer reflex quantification system characterizing response and latency. In: 31st Annual International Conference of the IEEE, Engineering in Medicine and Biology Society (EMBS), pp 5283–5286
11.
LeMoyne R, Mastroianni T, Kale H, Luna J, Stewart J, Elliot S, Bryan F, Coroian C, Grundfest W (2011) Fourth generation wireless reflex quantification system for acquiring tendon reflex response and latency. J Mech Med Bio 11(01):31–54CrossRef
12.
LeMoyne R, Coroian C, Mastroianni T, Grundfest W (2009) Wireless accelerometer assessment of gait for quantified disparity of hemiparetic locomotion. J Mech Med Bio 9(03):329–343CrossRef
13.
LeMoyne R, Coroian C, Mastroianni T (2009) Wireless accelerometer system for quantifying gait. In: ICME International Conference on IEEE, Complex Medical Engineering (CME), pp 1–4
14.
LeMoyne R, Mastroianni T, Grundfest W (2013) Wireless accelerometer system for quantifying disparity of hemiplegic gait using the frequency domain. J Mech Med Bio 13(03):1350035CrossRef
15.
LeMoyne R, Coroian C, Mastroianni T, Grundfest W (2008) Virtual proprioception. J Mech Med Bio 8(03):317–338CrossRef
16.
LeMoyne R, Coroian C, Mastroianni T, Wu W, Grundfest W, Kaiser W (2008) Virtual proprioception with real-time step detection and processing. In: 30th Annual International Conference of the IEEE, Engineering in Medicine and Biology Society (EMBS), pp 4238–4241
17.
LeMoyne R, Mastroianni T (2015) Use of smartphones and portable media devices for quantifying human movement characteristics of gait, tendon reflex response, and Parkinson’s disease hand tremor. Methods and Protocols, Mobile Health Technologies, 335–358
18.
LeMoyne R, Mastroianni T (2017) Wearable and wireless gait analysis platforms: smartphones and portable media devices. Wireless MEMS Networks and Applications, 129–152
19.
LeMoyne R, Mastroianni T (2016) Telemedicine perspectives for wearable and wireless applications serving the domain of neurorehabilitation and movement disorder treatment. Telemedicine, 1–10
20.
LeMoyne R (2016) Testing and evaluation strategies for the powered prosthesis, a global perspective. Advances for Prosthetic Technology: From Historical Perspective to Current Status to Future Application, 37–58
21.
LeMoyne R, Mastroianni T, Cozza M, Coroian C, Grundfest W (2010) Implementation of an iPhone as a wireless accelerometer for quantifying gait characteristics. In: 32nd Annual International Conference of the IEEE, Engineering in Medicine and Biology Society (EMBS), pp 3847–3851
22.
LeMoyne R, Mastroianni T, Cozza M, Coroian C (2010) iPhone wireless accelerometer application for acquiring quantified gait attributes. In: ASME 2010 5th Frontiers in Biomedical Devices Conference, American Society of Mechanical Engineers, pp 19–20
23.
LeMoyne R, Mastroianni T, Cozza M, Coroian C (2010) Quantification of gait characteristics through a functional iPhone wireless accelerometer application mounted to the spine. In: ASME 2010 5th Frontiers in Biomedical Devices Conference, American Society of Mechanical Engineers, pp 87–88
24.
LeMoyne R, Mastroianni T (2014) Quantification of patellar tendon reflex response using an iPod wireless gyroscope application with experimentation conducted in Lhasa, Tibet and post-processing conducted in Flagstaff, Arizona through wireless Internet connectivity. In: 44th Society for Neuroscience Annual Meeting
25.
LeMoyne R, Mastroianni T, Grundfest W (2011) Wireless accelerometer iPod application for quantifying gait characteristics. In: 33rd Annual International Conference of the IEEE, Engineering in Medicine and Biology Society (EMBS), pp 7904–7907
26.
LeMoyne R, Mastroianni T (2014) Implementation of an iPod application as a wearable and wireless accelerometer system for identifying quantified disparity of hemiplegic gait. J Med Imag Health Inform 4(4):634–641CrossRef
27.
LeMoyne R, Mastroianni T, Montoya K (2014) Implementation of a smartphone for evaluating gait characteristics of a trans-tibial prosthesis. In: 36th Annual International Conference of the IEEE, Engineering in Medicine and Biology Society (EMBS), pp 3674–3677
28.
LeMoyne R, Mastroianni T (2016) Implementation of a smartphone as a wireless gyroscope platform for quantifying reduced arm swing in hemiplegic gait with machine learning classification by multilayer perceptron neural network. In: 38th Annual International Conference of the IEEE, Engineering in Medicine and Biology Society (EMBS), pp 2626–2630
29.
Mastroianni T, LeMoyne R (2016) Application of a multilayer perceptron neural network with an iPod as a wireless gyroscope platform to classify reduced arm swing gait for people with Erb’s palsy. In: 46th Society for Neuroscience Annual Meeting
30.
LeMoyne R, Mastroianni T, Grundfest W (2012) Quantified reflex strategy using an iPod as a wireless accelerometer application. In: 34th Annual International Conference of the IEEE, Engineering in Medicine and Biology Society (EMBS), pp 2476–2479
31.
LeMoyne R, Mastroianni T (2011) Reflex response quantification using an iPod wireless accelerometer application. In: 41st Society for Neuroscience Annual Meeting
32.
LeMoyne R, Kerr WT, Zanjani K, Mastroianni T (2014) Implementation of an iPod wireless accelerometer application using machine learning to classify disparity of hemiplegic and healthy patellar tendon reflex pair. J Med Imag Health Inform 4(1):21–28CrossRef
33.
LeMoyne R, Mastroianni T, Grundfest W, Nishikawa K (2013) Implementation of an iPhone wireless accelerometer application for the quantification of reflex response. In: 35th Annual International Conference of the IEEE, Engineering in Medicine and Biology Society (EMBS), pp 4658–4661
34.
LeMoyne R, Mastroianni T (2014) Implementation of a smartphone as a wireless gyroscope application for the quantification of reflex response. In: 36th Annual International Conference of the IEEE, Engineering in Medicine and Biology Society (EMBS), pp 3654–3657
35.
LeMoyne R, Mastroianni T (2015) Machine learning classification of a hemiplegic and healthy patellar tendon reflex pair through an iPod wireless gyroscope platform. In: 45th Society for Neuroscience Annual Meeting
36.
LeMoyne R, Mastroianni T (2016) Implementation of a multilayer perceptron neural network for classifying a hemiplegic and healthy reflex pair using an iPod wireless gyroscope platform. In: 46th Society for Neuroscience Annual Meeting
37.
LeMoyne R, Mastroianni T (2016) Smartphone wireless gyroscope platform for machine learning classification of hemiplegic patellar tendon reflex pair disparity through a multilayer perceptron neural network. In: Wireless Health (WH) of IEEE, pp 1–6
38.
LeMoyne R, Mastroianni T (2017) Implementation of a smartphone wireless gyroscope platform with machine learning for classifying disparity of a hemiplegic patellar tendon reflex pair. J Mech Med Bio (Online Ready):1750083
39.
40.
LeMoyne R, Heerinckx F, Aranca T, De Jager R, Zesiewicz T, Saal HJ (2016) Wearable body and wireless inertial sensors for machine learning classification of gait for people with Friedreich’s ataxia. In: IEEE 13th International Conference on Wearable and Implantable Body Sensor Networks (BSN), pp 147–151
41.
42.
Prajapati SK, Gage WH, Brooks D, Black SE, McIlroy WE (2011) A novel approach to ambulatory monitoring: investigation into the quantity and control of everyday walking in patients with subacute stroke. Neurorehabilitation Neural Repair 25(1):6–14CrossRef
43.
Guo Y, Wu D, Liu G, Zhao G, Huang B, Wang L (2012) A low-cost body inertial-sensing network for practical gait discrimination of hemiplegia patients. Telemed e-Health 18(10):748–754CrossRef
44.
González I, Fontecha J, Hervás R, Bravo J (2015) An ambulatory system for gait monitoring based on wireless sensorized insoles. Sensors 15(7):16589–16613CrossRef
45.
Wagner R, Ganz A (2012) PAGAS: portable and accurate gait analysis system. In:34th Annual International Conference of the IEEE, Engineering in Medicine and Biology Society (EMBS), pp 280–283
46.
Pu F, Fan X, Yang Y, Chen W, Li S, Li D, Fan Y (2014) Feedback system based on plantar pressure for monitoring Toe-walking strides in children with Cerebral Palsy. Am J Phys Med Rehabil 93(2):122–129CrossRef
47.
Casamassima F, Ferrari A, Milosevic B, Ginis P, Farella E, Rocchi L (2014) A wearable system for gait training in subjects with Parkinson’s disease. Sensors 14(4):6229–6246CrossRef
48.
Rosevall J, Rusu C, Talavera G, Carrabina J, Garcia J, Carenas C, Breuil F, Reixach E, Torrent M, Burkard S (2014) A wireless sensor insole for collecting gait data. Stud Heal Technol Inf 30(200):176–178
49.
50.
Rebula JR, Ojeda LV, Adamczyk PG, Kuo AD (2013) Measurement of foot placement and its variability with inertial sensors. Gait Posture 38(4):974–980CrossRef
51.
Swan M (2012) Sensor mania! the Internet of Things, wearable computing, objective metrics, and the quantified self 2.0. J Sens Actuator Netw 1(3):217–253
52.
LeMoyne R (2016) Future and advanced concepts for the powered prosthesis. Advances for Prosthetic Technology: From Historical Perspective to Current Status to Future Application, 127–130
Metadaten
Titel
Bluetooth Inertial Sensors for Gait and Reflex Response Quantification with Perspectives Regarding Cloud Computing and the Internet of Things
verfasst von
Robert LeMoyne
Timothy Mastroianni
Copyright-Jahr
2018
Verlag
Springer Singapore
Buch
Wearable and Wireless Systems for Healthcare I

Print ISBN: 978-981-10-5683-3

Electronic ISBN: 978-981-10-5684-0

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-981-10-5684-0_7

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