Smart Sensing System for the Detection of Specific Human Motion Symptoms of the Parkinson’s Disease

A. Kita, P. Lorenzi, G. Romano, R. Rao, R. Parisi, A. Suppa, M. Bologna, A. Berardelli, F. Irrera

2016

Abstract

We propose two different wearable wireless sensing systems based on Inertial Measurement Units for the home monitoring of specific symptoms of the Parkinson’s disease. In one configuration just one sensor is inserted in a headset, in the other configuration two sensors are positioned on the patient’s shins. They recognize and classify noticeable motion disorders potentially dangerous for patients and give an audio feedback. The systems use dedicated algorithms for real time processing of the raw signals from accelerometers and gyroscopes, one of which is based on an artificial neural network and another on a time-based analysis. The headset system detects satisfactorily a wide class of motion irregularities including the trunk disorders, but is poorly reliable on Parkinson’s patients. The other system with sensors on the shins provides an early detection of the freezing of gait with excellent performance in terms of sensitivity and precision, and timely provides a rhythmic auditory stimulation to the patient for releasing the involuntary block state.

References

  1. Arias, P. and Cudeiro, J. "Effect of Rhythmic Auditory Stimulation on Gait in Parkinsonian Patients with and without Freezing of Gait" PLoS ONE. Vol.5 (2010).
  2. Atallah, L., et al. "Gait asymmetry detection in older adults using a light ear-worn sensor." Physiological measurement 35.5 (2014): N29.
  3. Bachlin, M. et al. "A wearable system to assist walking of Parkinson s disease patients" Methods Inf Med, vol.49, pp.88-95, 2010.
  4. Bishop, C.M. et al. “Neural networks for pattern recognition. Clarendon, Oxford (1995).
  5. Bloem, B.R. et al. "Falls and freezing of gait in Parkinson's disease: a review of two interconnected, episodic phenomena." Movement Disorders 19.8 (2004): 871- 884.
  6. Chau T. “A review of analytical techniques for gait data” Part 2: neural network and wavelet methods. Gait & Posture. Vol.13 (2001) 102-120.
  7. Cola, G. et al. "An On-Node Processing Approach for Anomaly Detection in Gait." Sensors Journal, IEEE , vol.15, no.11, pp.6640-6649, Nov. (2015).
  8. Comotti, D. et al. "neMEMSi: One step forward in wireless attitude and heading reference systems" Inertial Sensors and Systems (ISISS), Intern. Symposium on 1-4 (2014).
  9. Keogh E. and Ratanamahatana C. A.: Exact indexing of dynamic time warping. Knowledge and information systems. Vol.7 (2005) 358-386.
  10. Kline D. M. and Berardi V. L.: Revisiting squared-error and cross-entropy functions for training neural network classifiers. Neural Computing & Applications. Vol.14 (2005) 310-318.
  11. Kwon, Yuri, et al. "A practical method for the detection of freezing of gait in patients with Parkinson's disease." Clinical interventions in aging 9 (2014): 1709.
  12. Lorenzi, P. et al. “Wearable Wireless Inertial Sensors for Long-Time Monitoring of Specific Motor Symptoms in Parkinson's Disease” BIODEVICES 2015 - 8th Int. Conference on Biomedical Electronics and Devices, Proceedings; Part of 7th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2015, Lisbon (P) pp.168-173.
  13. Madgwick, S.O.H et al. "Estimation of IMU and MARG orientation using a gradient descent algorithm", IEEE International Conference on Rehabilitation Robotics , Rehab Week Zurich, ETH Zurich Science City, Switzerland, 2011.
  14. Mazilu, S. et al. "Feature learning for detection and prediction of freezing of gait in Parkinson's disease." Machine Learning and Data Mining in Pattern Recognition. Springer Berlin Heidelberg, 2013. 144- 158.
  15. Mazilu, S. et al. "GaitAssist: A Daily-life Support and Training System for Parkinson's Disease Patients with Freezing of Gait", Proceedings of the SIGCHI Conference on Human Factors in Computing Systems 2531-2540 (2014).
  16. Moore, S. et al. "Autonomous identification of freezing of gait in Parkinson's disease from lower-body segmental accelerometry" Journal of NeuroEngineering and Rehabilitation, vol.10, pp.19, 2013.
  17. Nieuwboer, A. et al. "Abnormalities of the spatiotemporal characteristics of gait at the onset of freezing in Parkinson's disease." Movement Disorders 16.6 (2001): 1066-1075.
  18. Sijobert, B. et al. "IMU Based Detection of Freezing of Gait and Festination in Parkinson's Disease" IFESS MALAYSIA, 2014.
  19. Spildooren, J. et al "Freezing of gait in Parkinson's disease: the impact of dual tasking and turning" Movement Disorders25.15 (2010)2563-70.
  20. Wang, Kongming, et al. Alignment of curves by dynamic time warping. The Annals of Statistics, (1997), 25.3: 1251-1276.
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Paper Citation


in Harvard Style

Kita A., Lorenzi P., Romano G., Rao R., Parisi R., Suppa A., Bologna M., Berardelli A. and Irrera F. (2016). Smart Sensing System for the Detection of Specific Human Motion Symptoms of the Parkinson’s Disease . In Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIODEVICES, (BIOSTEC 2016) ISBN 978-989-758-170-0, pages 152-159. DOI: 10.5220/0005666801520159


in Bibtex Style

@conference{biodevices16,
author={A. Kita and P. Lorenzi and G. Romano and R. Rao and R. Parisi and A. Suppa and M. Bologna and A. Berardelli and F. Irrera},
title={Smart Sensing System for the Detection of Specific Human Motion Symptoms of the Parkinson’s Disease},
booktitle={Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIODEVICES, (BIOSTEC 2016)},
year={2016},
pages={152-159},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005666801520159},
isbn={978-989-758-170-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIODEVICES, (BIOSTEC 2016)
TI - Smart Sensing System for the Detection of Specific Human Motion Symptoms of the Parkinson’s Disease
SN - 978-989-758-170-0
AU - Kita A.
AU - Lorenzi P.
AU - Romano G.
AU - Rao R.
AU - Parisi R.
AU - Suppa A.
AU - Bologna M.
AU - Berardelli A.
AU - Irrera F.
PY - 2016
SP - 152
EP - 159
DO - 10.5220/0005666801520159