Issuu

International Research Journal of Engineering and Technology (IRJET)

e-ISSN: 2395-0056

Volume: 09 Issue: 05 | May 2022

p-ISSN: 2395-0072

www.irjet.net

Parkinson Hand-Tremor Recognition Using CNN+LSTM : A Brief Review Rutvik P. Patil1, Dr. Narendra M. Patel2, Mosin I. Hasan3 1PG

Student, Department of Computer Engineering, Birla Vishvakarma Mahavidyalaya, Anand, Gujarat, India Department of Computer Engineering, Birla Vishvakarma Mahavidyalaya, Anand, Gujarat, India ---------------------------------------------------------------------***-------------------------------------------------------------------Abstract- Parkinson's disease is a nervous system2,3Professors,

Existing approaches to tremor analysis necessitate the use of specialised sensors, which makes them difficult to implement in practise. Furthermore, the more high-level tremor diagnosis problem or tremor/no-tremor classification is the targeted application of these methodologies.[2] Computer vision assessments of gait[3] and wearable data analyses[4] have already showed potential in detecting Parkinson's disease during motor tasks. However, there are still a number of issues to be resolved[5].

related movement disorder. A scarcely apparent tremor in only one hand could be the first sign. Tremors are common, however they're frequently accompanied by stiffness or decreased mobility. The symptoms and indicators of Parkinson's disease vary from person to person. Early warning signs may be imperceptible and go unnoticed. Even when symptoms begin to affect both sides of your body, they usually begin on one side and progress to the other. Tremor, Slowed Movement, Rigid Muscles, Impaired Posture and Balance, Loss of Automatic Movement, Speech Changes, Writing Changes, and others are some of the signs and symptoms of Parkinson's disease. There are currently no particular tests available to diagnose Parkinson's disease. Parkinson's disease is diagnosed by a trained specialist in the field of nervous system conditions based on the patient's medical history, signs and symptoms, and a neurological and physical examination. For non-invasive monitoring, analysis, and diagnosis of individuals with motor disorders like Parkinson's disease, tremor estimation from video is crucial. Since the COVID-19 event, remote and objective assessment of Parkinson's disease motor symptoms has gotten a lot of attention. Many ways for diagnosing Parkinson's disease are discussed in this publication, as well as the technology, tools, and picture datasets used in the study.

The main objective is to recognize the human hand tremors from videos obtained with standard consumer RGB cameras. The problem is critical in medical applications for assisting medical workers in the monitoring and diagnosis of patients with motor disorders. Traditionally, clinical practise has relied on body-worn accelerometers, which provide accurate measurements but are obtrusive, time consuming to set up, and only allow for the monitoring of a single location per accelerometer. When accelerometers are replaced with a standard RGB camera, a nonintrusive means of measuring full-body tremors emerges, providing a significant advantage in clinical practise.

Literature Survey

Introduction

Silvia L. Pintea et al, in their paper “Hand-tremor frequency estimation in videos”[2], propose two different approaches for measuring human hand-tremor frequencies: (a) Lagrangian handtremor frequency estimation, which assesses the hand-tremor frequency using the trajectory of the hand motion in the image plane throughout the video; and (b) Eulerian hand-tremor frequency estimation. In Lagrangian method, they first apply the Kalman-filter tracker to the initialised hand locations detected by the pose estimation algorithm. Through this they obtain corrected locations of hand trajectory on which a windowed fourier transform function is applied which provides the PSD (Power Spectrum Density) Function. The maximum frequency is used as the estimated hand tremor frequency. Figure 2.1 shows how hand location changes with tremor and how lagrangian method is used to estimate tremor frequency.

Parkinson disease, commonly known as Tremor, is caused by a decrease in dopamine levels in the brain, which affects a person's motor functions, or physical functioning. With the passage of time, the neurons in a person's body begin to die and become irreplaceable. The effects of neurological problems and the decrease in dopamine levels in the body in patients show gradually, making it difficult to detect until the patient's condition requires medical treatment. However, the symptoms and severity levels vary from person to person. Voice loss, loss of balance, and unstable posture are some of the symptoms. According to the World Health Organization, 10 million people worldwide are diagnosed with Parkinson's disease each year. The risk of developing Parkinson's disease rises with age; today, 4% of Parkinson's disease sufferers worldwide are under the age of 50. Parkinson's disease affects 7 to 10 million people globally every year, according to estimates.[1]

Impact Factor value: 7.529

ISO 9001:2008 Certified Journal

Page 690