Mediaboss Marketing

Liang, T.-W. & Tarsy, D. In Up to Date (ed. Post, T. W.) (UpToDate, 2021).

Powers, R. et al. Smartwatch inertial sensors continuously monitor real-world motor fluctuations in Parkinsons disease. Sci. Transl. Med. 13, eabd7865 (2021).

Rovini, E., Maremmani, C. & Cavallo, F. How wearable sensors can support Parkinsons disease diagnosis and treatment: a systematic review. Front. Neurosci. 11, 555 (2017).

Kovosi, S. & Freeman, M. Administering medications for Parkinsons disease on time. Nursing 41, 66 (2011).

PubMed Google Scholar

Grissinger, M. Delayed administration and contraindicated drugs place hospitalized Parkinsons disease patients at. Risk. P T 43, 1039 (2018).

PubMed Google Scholar

Groiss, S. J., Wojtecki, L., Sdmeyer, M. & Schnitzler, A. Deep brain stimulation in Parkinsons disease. Ther. Adv. Neurol. Disord. 2, 2028 (2009).

CAS PubMed PubMed Central Google Scholar

Movement Disorder Society Task Force on Rating Scales for Parkinsons Disease. The unified Parkinsons disease Rating Scale (UPDRS): status and recommendations. Mov. Disord. 18, 738750 (2003).

Google Scholar

Goetz, C. G. et al. Movement Disorder Society-sponsored revision of the Unified Parkinsons Disease Rating Scale (MDS-UPDRS): Process, format, and clinimetric testing plan. Mov. Disord. 22, 4147 (2007).

PubMed Google Scholar

Louis, E. D. et al. Clinical correlates of action tremor in Parkinson disease. Arch. Neurol. 58, 1630 (2001).

CAS PubMed Google Scholar

Heldman, D. A. et al. The Modified Bradykinesia Rating Scale for Parkinsons disease: reliability and comparison with kinematic measures. Mov. Disord. 26, 18591863 (2011).

PubMed PubMed Central Google Scholar

Bathien, N., Koutlidis, R. M. & Rondot, P. EMG patterns in abnormal involuntary movements induced by neuroleptics. J. Neurol. Neurosurg. Psychiatry 47, 10021008 (1984).

CAS PubMed PubMed Central Google Scholar

Andrews, C. J. Influence of dystonia on the response to long-term L-dopa therapy in Parkinsons disease. J. Neurol. Neurosurg. Psychiatry 36, 630636 (1973).

CAS PubMed PubMed Central Google Scholar

Milner-Brown, H. S., Fisher, M. A. & Weiner, W. J. Electrical properties of motor units in Parkinsonism and a possible relationship with bradykinesia. J. Neurol. Neurosurg. Psychiatry 42, 3541 (1979).

CAS PubMed PubMed Central Google Scholar

Hacisalihzade, S. S., Albani, C. & Mansour, M. Measuring parkinsonian symptoms with a tracking device. Comput. Methods Prog. Biomed. 27, 257268 (1988).

CAS Google Scholar

Beuter, A., de Geoffroy, A. & Cordo, P. The measurement of tremor using simple laser systems. J. Neurosci. Methods 53, 4754 (1994).

CAS PubMed Google Scholar

Weller, C. et al. Defining small differences in efficacy between anti-parkinsonian agents using gait analysis: a comparison of two controlled release formulations of levodopa/decarboxylase inhibitor. Br. J. Clin. Pharm. 35, 379385 (1993).

CAS Google Scholar

OSuilleabhain, P. E. & Dewey, R. B. Validation for tremor quantification of an electromagnetic tracking device. Mov. Disord. 16, 265271 (2001).

PubMed Google Scholar

Deuschl, G., Lauk, M. & Timmer, J. Tremor classification and tremor time series analysis. Chaos: Interdiscip. J. Nonlinear Sci. 5, 48 (1998).

Google Scholar

Spyers-Ashby, J. M., Stokes, M. J., Bain, P. G. & Roberts, S. J. Classification of normal and pathological tremors using a multidimensional electromagnetic system. Med. Eng. Phys. 21, 713723 (1999).

CAS PubMed Google Scholar

Rajaraman, V. et al. A novel quantitative method for 3D measurement of Parkinsonian tremor. Clin. Neurophysiol. 111, 338343 (2000).

CAS PubMed Google Scholar

Hoff, J. I., van der Meer, V. & van Hilten, J. J. Accuracy of objective ambulatory accelerometry in detecting motor complications in patients with Parkinsons disease. Clin. Neuropharmacol. 27, 5357 (2004).

CAS PubMed Google Scholar

Dunnewold, R. J. W. et al. Ambulatory quantitative assessment of body position, bradykinesia, and hypokinesia in Parkinsons disease. J. Clin. Neurophysiol. 15, 235242 (1998).

CAS PubMed Google Scholar

Hoff, J. I., van den Plas, A. A., Wagemans, E. A. & van Hilten, J. J. Accelerometric assessment of levodopa-induced dyskinesias in Parkinsons disease. Mov. Disord. 16, 5861 (2001).

CAS PubMed Google Scholar

Dunnewold, R. J. W., Jacobi, C. E. & van Hilten, J. J. Quantitative assessment of bradykinesia in patients with Parkinsons disease. J. Neurosci. Methods 74, 107112 (1997).

CAS PubMed Google Scholar

Salarian, A. et al. Quantification of tremor and bradykinesia in Parkinsons disease using a novel ambulatory monitoring system. IEEE Trans. Biomed. Eng. 54, 313322 (2007).

PubMed Google Scholar

Mera, T. O., Heldman, D. A., Espay, A. J., Payne, M. & Giuffrida, J. P. Feasibility of home-based automated Parkinsons disease motor assessment. J. Neurosci. Methods 203, 152156 (2012).

PubMed Google Scholar

Heldman, D. A. et al. Automated motion sensor quantification of gait and lower extremity Bradykinesia. Conf. Proc. IEEE Eng. Med Biol. Soc. 2012, 19561959 (2012).

PubMed Central Google Scholar

Phan, D., Horne, M., Pathirana, P. N. & Farzanehfar, P. Measurement of axial rigidity and postural instability using wearable sensors. Sensors (Basel) 18, 495 (2018).

Salarian, A. et al. Analyzing 180 turns using an inertial system reveals early signs of progress in Parkinsons Disease. Conf. Proc. IEEE Eng. Med Biol. Soc. 2009, 224227 (2009).

PubMed Central Google Scholar

Moore, S. T. et al. Autonomous identification of freezing of gait in Parkinsons disease from lower-body segmental accelerometry. J. Neuroeng. Rehabil. 10, 19 (2013).

PubMed PubMed Central Google Scholar

Mancini, M. et al. Measuring freezing of gait during daily-life: an open-source, wearable sensors approach. J. Neuroeng. Rehabil. 18, 1 (2021).

PubMed PubMed Central Google Scholar

Reches, T. et al. Using wearable sensors and machine learning to automatically detect freezing of gait during a FOG-Provoking test. Sensors (Basel) 20, 4474 (2020).

Tripoliti, E. E. et al. Automatic detection of freezing of gait events in patients with Parkinsons disease. Comput. Methods Prog. Biomed. 110, 1226 (2013).

Google Scholar

Zach, H. et al. Identifying freezing of gait in Parkinsons disease during freezing provoking tasks using waist-mounted accelerometry. Parkinsonism. Relat. Disord. 21, 13621366 (2015).

PubMed Google Scholar

Manson, A. et al. An ambulatory dyskinesia monitor. J. Neurol. Neurosurg. Psychiatry 68, 196201 (2000).

CAS PubMed PubMed Central Google Scholar

Pulliam, C. L. et al. Continuous assessment of levodopa response in Parkinsons disease using wearable motion sensors. IEEE Trans. Biomed. Eng. 65, 159164 (2018).

PubMed Google Scholar

Rodrguez-Molinero, A. et al. Estimating dyskinesia severity in Parkinsons disease by using a waist-worn sensor: concurrent validity study. Sci. Rep. 9, 13434 (2019).

Giovannoni, G., van Schalkwyk, J., Fritz, V. & Lees, A. Bradykinesia akinesia inco-ordination test (BRAIN TEST): an objective computerised assessment of upper limb motor function. J. Neurol. Neurosurg. Psychiatry 67, 624629 (1999).

CAS PubMed PubMed Central Google Scholar

Allen, D. P. et al. On the use of low-cost computer peripherals for the assessment of motor dysfunction in Parkinsons diseasequantification of bradykinesia using target tracking tasks. IEEE Trans. Neural Syst. Rehabilitation Eng. 15, 286294 (2007).

CAS Google Scholar

Espay, A. J. et al. At-home training with closed-loop augmented-reality cueing device for improving gait in patients with Parkinsons disease. J. Rehabil. Res. Dev. 47, 573 (2010).

PubMed Google Scholar

Bachlin, M. et al. Wearable assistant for Parkinsons disease patients with the freezing of gait symptom. IEEE Trans. Inf. Technol. Biomed. 14, 436446 (2010).

PubMed Google Scholar

Lee, A. et al. Can google glassTM technology improve freezing of gait in parkinsonism? A pilot study. Disabil. Rehabil. Assist. Technol. 111. https://doi.org/10.1080/17483107.2020.1849433 (2020).

Rao, A. S. et al. Quantifying drug induced dyskinesia in Parkinsons disease patients using standardized videos. In: 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society 17691772. https://doi.org/10.1109/IEMBS.2008.4649520 (2008).

van Hilten, J. J., Middelkoop, H. A., Kerkhof, G. A. & Roos, R. A. A new approach in the assessment of motor activity in Parkinsons disease. J. Neurol. Neurosurg. Psychiatry 54, 976979 (1991).

PubMed PubMed Central Google Scholar

Burne, J. A., Hayes, M. W., Fung, V. S. C., Yiannikas, C. & Boljevac, D. The contribution of tremor studies to diagnosis of Parkinsonian and essential tremor: a statistical evaluation. J. Clin. Neurosci. 9, 237242 (2002).

CAS PubMed Google Scholar

Cole, B. T., Roy, S. H., Luca, C. J. D. & Nawab, S. H. Dynamic neural network detection of tremor and dyskinesia from wearable sensor data. In: 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology 60626065. https://doi.org/10.1109/IEMBS.2010.5627618 (2010).

Tsipouras, M. G. et al. An automated methodology for levodopa-induced dyskinesia: assessment based on gyroscope and accelerometer signals. Artif. Intell. Med. 55, 127135 (2012).

PubMed Google Scholar

Papapetropoulos, S. et al. Objective quantification of neuromotor symptoms in Parkinsons disease: implementation of a portable, computerized measurement tool. Parkinsons Dis. 2010, (2010).

Yang, C.-C., Hsu, Y.-L., Shih, K.-S. & Lu, J.-M. Real-time gait cycle parameter recognition using a wearable accelerometry system. Sensors (Basel) 11, 73147326 (2011).

Google Scholar

Klucken, J. et al. Unbiased and mobile gait analysis detects motor impairment in Parkinsons disease. PLoS ONE 8, e56956 (2013).

Marcante, A. et al. Foot pressure wearable sensors for freezing of gait detection in Parkinsons disease. Sensors (Basel) 21, 128 (2020).

Mahadevan, N. et al. Development of digital biomarkers for resting tremor and bradykinesia using a wrist-worn wearable device. npj Digital Med. 3, 112 (2020).

Google Scholar

Heldman, D. A. et al. Telehealth management of Parkinsons disease using wearable Sensors: Exploratory Study. Digit Biomark. 1, 4351 (2017).

PubMed PubMed Central Google Scholar

Ferreira, J. J. et al. Quantitative home-based assessment of Parkinsons symptoms: the SENSE-PARK feasibility and usability study. BMC Neurol. 15, 89 (2015).

PubMed PubMed Central Google Scholar

Fisher, J. M., Hammerla, N. Y., Rochester, L., Andras, P. & Walker, R. W. Body-worn sensors in Parkinsons disease: evaluating their acceptability to patients. Telemed. J. E Health 22, 6369 (2016).

PubMed PubMed Central Google Scholar

Evers, L. J. et al. Real-life gait performance as a digital biomarker for motor fluctuations: the Parkinson@Home validation study. J. Med. Internet Res. 22, e19068 (2020).

Erb, M. K. et al. mHealth and wearable technology should replace motor diaries to track motor fluctuations in Parkinsons disease. npj Digital Med. 3, 110 (2020).

Here is the original post:
Co-evolution of machine learning and digital technologies to improve monitoring of Parkinson's disease motor symptoms | npj Digital Medicine -...