[1]
|
LeMoyne, R., Mastroianni, T., Cozza, M., Coroian, C. and Grundfest, W. (2010) Implementation of an iPhone for Characterizing Parkinson’s Disease Tremor through a Wireless Accelerometer Application. Proceedings of the 32nd Annual International Conference of the IEEE EMBS, Buenos Aires, 31 August-4 September 2010, 4954-4958. https://doi.org/10.1109/IEMBS.2010.5627240
|
[2]
|
LeMoyne, R. and Mastroianni, T. (2015) Chapter 23 Use of Smartphones and Portable Media Devices for Quantifying Human Movement Characteristics of Gait, Tendon Reflex Response, and Parkinson’s Disease Hand Tremor. In: Rasooly, A. and Herold, K.E., Eds., Mobile Health Technologies: Methods and Protocols, Springer, New York, 335-358. https://doi.org/10.1007/978-1-4939-2172-0_23
|
[3]
|
LeMoyne, R. and Mastroianni, T. (2017) Chapter 1 Smartphone and Portable Media Device: A Novel Pathway toward the Diagnostic Characterization of Human Movement. In: Mohamudally, N., Ed., Smartphones from an Applied Research Perspective, InTech, Rijeka, 1-24. https://doi.org/10.5772/intechopen.69961
|
[4]
|
LeMoyne, R. and Mastroianni, T. (2017) Chapter 6 Wearable and Wireless Gait Analysis Platforms: Smartphones and Portable Media Devices. In: Uttamchandani, D., Ed., Wireless MEMS Networks and Applications, Elsevier, New York, 129-152.
https://doi.org/10.1016/B978-0-08-100449-4.00006-3
|
[5]
|
LeMoyne, R. and Mastroianni, T. (2016) Telemedicine Perspectives for Wearable and Wireless Applications Serving the Domain of Neurorehabilitation and Movement Disorder Treatment. Telemedicine, SMGroup, Dover, 1-10.
|
[6]
|
LeMoyne, R., Mastroianni, T., McCandless, C., Currivan, C., Whiting, D. and Tomycz, N. (2018) Implementation of a Smartphone as a Wearable and Wireless Accelerometer and Gyroscope Platform for Ascertaining Deep Brain Stimulation Treatment Efficacy of Parkinson’s Disease through Machine Learning Classification. Advances in Parkinson’s Disease, 7, 19-30.
|
[7]
|
LeMoyne, R., Mastroianni, T., Whiting, D. and Tomycz, N. (2019) Wearable and Wireless Systems for Healthcare II. Springer, Singapore.
https://doi.org/10.1007/978-981-13-5808-1
|
[8]
|
LeMoyne, R., Mastroianni, T., Whiting, D. and Tomycz, N. (2019) Chapter 7 Wearable and Wireless Systems with Internet Connectivity for Quantification of Parkinson’s Disease and Essential Tremor Characteristics. In: Wearable and Wireless Systems for Healthcare II, Springer, Singapore, 79-97.
https://doi.org/10.1007/978-981-13-5808-1_7
|
[9]
|
LeMoyne, R., Mastroianni, T., Whiting, D. and Tomycz, N. (2019) Chapter 9 Assessment of Machine Learning Classification Strategies for the Differentiation of Deep Brain Stimulation “On” and “Off” Status for Parkinson’s Disease Using a Smartphone as a Wearable and Wireless Inertial Sensor for Quantified Feedback. In: Wearable and Wireless Systems for Healthcare II, Springer, Singapore, 113-126.
https://doi.org/10.1007/978-981-13-5808-1_9
|
[10]
|
MC10 Inc. https://www.mc10inc.com/our-products#biostamp-npoint
|
[11]
|
Jarchi, D., Pope, J., Lee, T.K., Tamjidi, L., Mirzaei, A. and Sanei, S. (2018) A Review on Accelerometry-Based Gait Analysis and Emerging Clinical Applications. IEEE Reviews in Biomedical Engineering, 11, 177-194.
https://doi.org/10.1109/RBME.2018.2807182
|
[12]
|
Dinesh, K., Xiong, M., Adams, J., Dorsey, R. and Sharma, G. (2016) Signal Analysis for Detecting Motor Symptoms in Parkinson’s and Huntington’s Disease Using Multiple Body-Affixed Sensors: A Pilot Study. IEEE Western New York Image and Signal Processing Workshop (WNYISPW), Rochester, 18 November 2016, 1-5.
https://doi.org/10.1109/WNYIPW.2016.7904834
|
[13]
|
Lonini, L., Dai, A., Shawen, N., Simuni, T., Poon, C., Shimanovich, L., Daeschler, M., Ghaffari, R., Rogers, J.A. and Jayaraman, A. (2018) Wearable Sensors for Parkinson’s Disease: Which Data Are Worth Collecting for Training Symptom Detection Models. NPJ Digital Medicine, 1, 1-8.
https://doi.org/10.1038/s41746-018-0071-z
|
[14]
|
Adams, J.L., Dinesh, K., Xiong, M., Tarolli, C.G., Sharma, S., Sheth, N., Aranyosi, A.J., Zhu, W., Goldenthal, S., Biglan, K.M. and Dorsey, E.R. (2017) Multiple Wearable Sensors in Parkinson and Huntington Disease Individuals: A Pilot Study in Clinic and at Home. Digital Biomarkers, 1, 52-63.
https://doi.org/10.1159/000479018
|
[15]
|
Thorp, J.E., Adamczyk, P.G., Ploeg, H.L. and Pickett, K.A. (2018) Monitoring Motor Symptoms during Activities of Daily Living in Individuals with Parkinson’s Disease. Frontiers in Neurology, 9, 1036. https://doi.org/10.3389/fneur.2018.01036
|
[16]
|
Wright, J.M., Regele, O.B., Kourtis, L.C., Pszenny, S.M., Sirkar, R., Kovalchick, C. and Jones, G.B. (2017) Evolution of the Digital Biomarker Ecosystem. Digital Medicine, 3, 154-163. https://doi.org/10.4103/digm.digm_35_17
|
[17]
|
Gibney, E. (2015) The Body Electric. Nature, 528, 26-28.
https://doi.org/10.1038/528026a
|
[18]
|
Sen-Gupta, E., Wright, D.E., Caccese, J.W., Wright Jr., J.A., Jortberg, E., Bhatkar, V., Ceruolo, M., Ghaffari, R., Clason, D.L., Maynard, J.P. and Combs, A.H. (2019) A Pivotal Study to Validate the Performance of a Novel Wearable Sensor and System for Biometric Monitoring in Clinical and Remote Environments. Digital Biomarkers, 3, 1-13. https://doi.org/10.1159/000493642
|
[19]
|
Mombers, C., Legako, K. and Gilchrist, A. (2016) Identifying Medical Wearables and Sensor Technologies that Deliver Data on Clinical Endpoints. British Journal of Clinical Pharmacology, 81, 196-198. https://doi.org/10.1111/bcp.12818
|
[20]
|
Kraemer, F.A., Braten, A.E., Tamkittikhun, N. and Palma, D. (2017) Fog Computing in Healthcare: A Review and Discussion. IEEE Access, 5, 9206-9222.
https://doi.org/10.1109/ACCESS.2017.2704100
|
[21]
|
Kandel, E.R., Schwartz, J.H. and Jessell, T.M. (2000) Chapter 43 Principles of Neural Science. McGraw-Hill, New York.
|
[22]
|
Seeley, R.R., Stephens, T.D. and Tate, P. (2003) Chapter 14 Anatomy and Physiology. McGraw-Hill, Boston.
|
[23]
|
Bickley, L.S. and Szilagyi, P.G. (2003) Chapter 16 Bates’ Guide to Physical Examination and History Taking. Lippincott Williams and Wilkins, Philadelphia.
|
[24]
|
Diamond, M.C., Scheibel, A.B. and Elson, L.M. (1985) Chapter 5 the Human Brain Coloring Book. Harper Perennial, New York.
|
[25]
|
Nolte, J. and Sundsten, J.W. (2002) Chapter 19 the Human Brain: An Introduction to Its Functional Anatomy. Mosby, St. Louis.
|
[26]
|
LeMoyne, R. (2013) Wearable and Wireless Accelerometer Systems for Monitoring Parkinson’s Disease Patients—A Perspective Review. Advances in Parkinson’s Disease, 2, 113-115. https://doi.org/10.4236/apd.2013.24021
|
[27]
|
Giller, C.A., Dewey, R.B., Ginsburg, M.I., Mendelsohn, D.B. and Berk, A.M. (1998) Stereotactic Pallidotomy and Thalamotomy Using Individual Variations of Anatomic Landmarks for Localization. Neurosurgery, 42, 56-65.
https://doi.org/10.1097/00006123-199801000-00011
|
[28]
|
Niranjan, A., Kondziolka, D., Baser, S., Heyman, R. and Lunsford, L.D. (2000) Functional Outcomes after Gamma Knife Thalamotomy for Essential Tremor and MS-Related Tremor. Neurology, 55, 443-446. https://doi.org/10.1212/WNL.55.3.443
|
[29]
|
Young, R.F., Jacques, S., Mark, R., Kopyov, O., Copcutt, B., Posewitz, A. and Li, F. (2000) Gamma Knife Thalamotomy for Treatment of Tremor: Long-Term Results. Journal of Neurosurgery, 93, 128-135.
https://doi.org/10.3171/jns.2000.93.supplement_3.0128
|
[30]
|
Williams, R. (2010) Alim-Louis Benabid: Stimulation and Serendipity. Lancet Neurology, 9, 1152. https://doi.org/10.1016/S1474-4422(10)70291-X
|
[31]
|
Miocinovic, S., Somayajula, S., Chitnis, S. and Vitek, J.L. (2013) History, Applications, and Mechanisms of Deep Brain Stimulation. JAMA Neurology, 70, 163-171.
https://doi.org/10.1001/2013.jamaneurol.45
|
[32]
|
Benabid, A.L., Pollak, P., Louveau, A., Henry, S. and de Rougemont, J. (1987) Combined (Thalamotomy and Stimulation) Stereotactic Surgery of the VIM Thalamic Nucleus for Bilateral Parkinson Disease. Applied Neurophysiology, 50, 344-346.
https://doi.org/10.1159/000100803
|
[33]
|
Amon, A. and Alesch, F. (2017) Systems for Deep Brain Stimulation: Review of Technical Features. Journal of Neural Transmission, 124, 1083-1091.
https://doi.org/10.1007/s00702-017-1751-6
|
[34]
|
Yu, H. and Neimat, J.S. (2008) The Treatment of Movement Disorders by Deep Brain Stimulation. Neurotherapeutics, 5, 26-36.
https://doi.org/10.1016/j.nurt.2007.10.072
|
[35]
|
Volkmann, J., Moro, E. and Pahwa, R. (2006) Basic Algorithms for the Programming of Deep Brain Stimulation in Parkinson’s Disease. Movement Disorders, 21, S284-S289. https://doi.org/10.1002/mds.20961
|
[36]
|
Isaias, I.U. and Tagliati, M. (2008) Chapter 20 Deep Brain Stimulation Programming for Movement Disorders. In: Tarsy, D., Vitek, J.L., Starr, P.A. and Okun, M.S., Eds., Deep Brain Stimulation in Neurological and Psychiatric Disorders, Springer, New York, 361-397. https://doi.org/10.1007/978-1-59745-360-8_20
|
[37]
|
Pretto, T. (2007) Deep Brain Stimulation. Neurologist, 13, 103-104.
https://doi.org/10.1097/01.nrl.0000258304.16124.e5
|
[38]
|
LeMoyne, R., Mastroianni, T., Whiting, D. and Tomycz, N. (2019) Chapter 3 Traditional Ordinal Strategies for Establishing the Severity and Status of Movement Disorders, Such as Parkinson’s Disease and Essential Tremor. In: Wearable and Wireless Systems for Healthcare II, Springer, Singapore, 25-36.
https://doi.org/10.1007/978-981-13-5808-1_3
|
[39]
|
LeMoyne, R., Coroian, C., Mastroianni, T., Opalinski, P., Cozza, M. and Grundfest, W. (2009) Chapter 10 the Merits of Artificial Proprioception, with Applications in Biofeedback Gait Rehabilitation Concepts and Movement Disorder Characterization. In: Barros de Mello, C.A., Ed., Biomedical Engineering, InTech, Vienna, 165-198. https://doi.org/10.5772/7883
|
[40]
|
Ramaker, C., Marinus, J., Stiggelbout, A.M. and Van Hilten, B.J. (2002) Systematic Evaluation of Rating Scales for Impairment and Disability in Parkinson’s Disease. Movement Disorders, 17, 867-876. https://doi.org/10.1002/mds.10248
|
[41]
|
Goetz, C.G., Stebbins, G.T., Chmura, T.A., Fahn, S., Poewe, W. and Tanner, C.M. (2010) Teaching Program for the Movement Disorder Society-Sponsored Revision of the Unified Parkinson’s Disease Rating Scale: (MDS-UPDRS). Movement Disorders, 25, 1190-1194. https://doi.org/10.1002/mds.23096
|
[42]
|
Movement Disorder Society Task Force on Rating Scales for Parkinson’s Disease (2003) The Unified Parkinson’s Disease Rating Scale (UPDRS): Status and Recommendations. Movement Disorders, 18, 738-750. https://doi.org/10.1002/mds.10473
|
[43]
|
Post, B., Merkus, M.P., de Bie, R., de Haan, R.J. and Speelman, J.D. (2005) Unified Parkinson’s Disease Rating Scale Motor Examination: Are Ratings of Nurses, Residents in Neurology, and Movement Disorders Specialists Interchangeable? Movement Disorders, 20, 1577-1584. https://doi.org/10.1002/mds.20640
|
[44]
|
LeMoyne, R., Mastroianni, T., Whiting, D. and Tomycz, N. (2019) Chapter 6 Preliminary Wearable and Locally Wireless Systems for Quantification of Parkinson’s Disease and Essential Tremor Characteristics. In: Wearable and Wireless Systems for Healthcare II, Springer, Singapore, 65-78.
https://doi.org/10.1007/978-981-13-5808-1_6
|
[45]
|
Schrag, A., Schelosky, L., Scholz, U. and Poewe, W. (1999) Reduction of Parkinsonian Signs in Patients with Parkinson’s Disease by Dopaminergic versus Anticholinergic Single-Dose Challenges. Movement Disorders, 14, 252-255.
https://doi.org/10.1002/1531-8257(199903)14:2<252::AID-MDS1009>3.0.CO;2-N
|
[46]
|
Keijsers, N.L., Horstink, M.W., van Hilten, J.J., Hoff, J.I. and Gielen, C.C. (2000) Detection and Assessment of the Severity of Levodopa-Induced Dyskinesia in Patients with Parkinson’s Disease by Neural Networks. Movement Disorders, 15, 1104-1111.
https://doi.org/10.1002/1531-8257(200011)15:6<1104::AID-MDS1007>3.0.CO;2-E
|
[47]
|
Keijsers, N.L., Horstink, M.W. and Gielen, S.C. (2006) Ambulatory Motor Assessment in Parkinson’s Disease. Movement Disorders, 21, 34-44.
https://doi.org/10.1002/mds.20633
|
[48]
|
Gurevich, T.Y., Shabtai, H., Korczyn, A.D., Simon, E.S. and Giladi, N. (2006) Effect of Rivastigmine on Tremor in Patients with Parkinson’s Disease and Dementia. Movement Disorders, 21, 1663-1666. https://doi.org/10.1002/mds.20971
|
[49]
|
Obwegeser, A.A., Uitti, R.J., Witte, R.J., Lucas, J.A., Turk, M.F. and Wharen Jr., R.E. (2001) Quantitative and Qualitative Outcome Measures after Thalamic Deep Brain Stimulation to Treat Disabling Tremors. Neurosurgery, 48, 274-284.
https://doi.org/10.1227/00006123-200102000-00004
|
[50]
|
Kumru, H., Summerfield, C., Valldeoriola, F. and Valls-Solé, J. (2004) Effects of Subthalamic Nucleus Stimulation on Characteristics of EMG Activity Underlying Reaction Time in Parkinson’s Disease. Movement Disorders, 19, 94-100.
https://doi.org/10.1002/mds.10638
|
[51]
|
Patel, S., Park, H., Bonato, P., Chan, L. and Rodgers, M. (2012) A Review of Wearable Sensors and Systems with Application in Rehabilitation. Journal of NeuroEngineering and Rehabilitation, 9, 1-17. https://doi.org/10.1186/1743-0003-9-21
|
[52]
|
LeMoyne, R., Coroian, C. and Mastroianni, T. (2008) 3D Wireless Accelerometer Characterization of Parkinson’s Disease Status. Proceedings of the Plasticity and Repair in Neurodegenerative Disorders, Lake Arrowhead, May 2008.
|
[53]
|
LeMoyne, R., Coroian, C. and Mastroianni, T. (2009) Quantification of Parkinson’s Disease Characteristics Using Wireless Accelerometers. Proceeding of the International Conference on Complex Medical Engineering (CME-2009) of the IEEE/ICME, Tempe, 9-11 April 2009, 1-5. https://doi.org/10.1109/ICCME.2009.4906657
|
[54]
|
LeMoyne, R., Mastroianni, T. and Grundfest, W. (2013) Wireless Accelerometer Configuration for Monitoring Parkinson’s Disease Hand Tremor. Advances in Parkinson’s Disease, 2, 62-67. https://doi.org/10.4236/apd.2013.22012
|
[55]
|
Giuffrida, J.P., Riley, D.E., Maddux, B.N. and Heldman, D.A. (2009) Clinically Deployable Kinesia Technology for Automated Tremor Assessment. Movement Disorders, 24, 723-730. https://doi.org/10.1002/mds.22445
|
[56]
|
LeMoyne, R., Tomycz, N., Mastroianni, T., McCandless, C., Cozza, M. and Peduto, D. (2015) Implementation of a Smartphone Wireless Accelerometer Platform for Establishing Deep Brain Stimulation Treatment Efficacy of Essential Tremor with Machine Learning. Proceedings of the 37th Annual International Conference of the IEEE EMBS, Milan, 25-29 August 2015, 6772-6775.
https://doi.org/10.1109/EMBC.2015.7319948
|
[57]
|
LeMoyne, R., Mastroianni, T., Tomycz, N., Whiting, D., Oh, M., McCandless, C., Currivan, C. and Peduto, D. (2017) Implementation of a Multilayer Perceptron Neural Network for Classifying Deep Brain Stimulation in “On” and “Off” Modes through a Smartphone Representing a Wearable and Wireless Sensor Application. Proceedings of the 47th Annual Meeting of the Society for Neuroscience, Washington DC, 11-15 November 2017.
|
[58]
|
LeMoyne, R., Mastroianni, T., McCandless, C., Currivan, C., Whiting, D. and Tomycz, N. (2018) Implementation of a Smartphone as a Wearable and Wireless Inertial Sensor Platform for Determining Efficacy of Deep Brain Stimulation for Parkinson’s Disease Tremor through Machine Learning. Proceedings of the 48th Annual Meeting of the Society for Neuroscience (Nanosymposium), San Diego, 3-7 November 2018.
|
[59]
|
LeMoyne, R., Mastroianni, T., McCandless, C., Whiting, D. and Tomycz, N. (2019) Evaluation of Machine Learning Algorithms for Classifying Deep Brain Stimulation Respective of “On” and “Off” Status. Proceedings of the 9th International IEEE/EMBS Conference on Neural Engineering (NER), San Francisco, 20-23 March 2019, 483-488. https://doi.org/10.1109/NER.2019.8717095
|
[60]
|
LeMoyne, R. and Mastroianni, T. (2018) Wearable and Wireless Systems for Healthcare I. Springer, Singapore. https://doi.org/10.1007/978-981-10-5684-0
|
[61]
|
LeMoyne, R. and Mastroianni, T. (2018) Chapter 7 Bluetooth Inertial Sensors for Gait and Reflex Response Quantification with Perspectives Regarding Cloud Computing and the Internet of Things. In: Wearable and Wireless Systems for Healthcare I, Springer, Singapore, 95-103. https://doi.org/10.1007/978-981-10-5684-0_7
|
[62]
|
LeMoyne, R., Heerinckx, F., Aranca, T., De Jager, R., Zesiewicz, T. and Saal, H.J. (2016) Wearable Body and Wireless Inertial Sensors for Machine Learning Classification of Gait for People with Friedreich’s Ataxia. Proceedings of the 13th International Conference on Wearable and Implantable Body Sensor Networks, San Francisco, 14-17 June 2016, 147-151. https://doi.org/10.1109/BSN.2016.7516249
|
[63]
|
Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P. and Witten, I.H. (2009) The WEKA Data Mining Software: An Update. ACM SIGKDD Explorations Newsletter, 11, 10-18. https://doi.org/10.1145/1656274.1656278
|
[64]
|
Witten, I.H., Frank, E. and Hall, M.A. (2011) Data Mining: Practical Machine Learning Tools and Techniques. Morgan Kaufmann, Burlington.
|
[65]
|
WEKA. http://www.cs.waikato.ac.nz/~ml/weka
|
[66]
|
LeMoyne, R. and Mastroianni, T. (2017) Virtual Proprioception for Eccentric Training. Proceedings of the 39th Annual International Conference of the IEEE EMBS, Jeju Island, 11-15 July 2017, 4557-4561.
https://doi.org/10.1109/EMBC.2017.8037870
|
[67]
|
LeMoyne, R. and Mastroianni, T. (2017) Wireless Gyroscope Platform Enabled by a Portable Media Device for Quantifying Wobble Board Therapy. Proceedings of the 39th Annual International Conference of the IEEE EMBS, Jeju Island, 11-15 July 2017, 2662-2666. https://doi.org/10.1109/EMBC.2017.8037405
|
[68]
|
LeMoyne, R. and 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. Proceedings of the 38th Annual International Conference of the IEEE EMBS, Orlando, 16-20 August 2016, 2626-2630.
https://doi.org/10.1109/EMBC.2016.7591269
|
[69]
|
LeMoyne, R., Mastroianni, T., Whiting, D. and Tomycz, N. (2019) Chapter 10 New Perspectives for Network Centric Therapy for the Treatment of Parkinson’s Disease and Essential Tremor. In: Wearable and Wireless Systems for Healthcare II, Springer, Singapore, 127-128. https://doi.org/10.1007/978-981-13-5808-1_10
|