## 2 State of the Art and Task Description  
### State of the Art in Parkinsonian Tremor Quantification  
Some research groups have used infrared cameras, video tracking, digital drawing tablets, laser-based displacement transducers, and electromyography (EMG) to assess tremors objectively [1; 2; 3; 4; 5; 6; 7; 8; 9; 10]. Sensors were placed on the body, feet or arms of the patient. Most of these sensor-based systems could detect the change between therapy \"OFF\" and \"ON\" states during medication. However, because these systems have big dimensions or patients were uncomfortable wearing such devices, such systems have limited usability in clinical applications [7].  
At present, most tremor assessment methods were based on inertial sensors and a computer-based system. There has recently been growing interest in the application of MEMS (Micro-Electro-Mechanical Systems) inertial sensors for continuous monitoring of PD symptoms. With the development of new MEMS technology, the dimension of the sensor circuit board is smaller and signal processing is easier to carry out than before [5].  
Some studies have indicated that sensor data from accelerometers and gyroscopes correlate strongly with UPDRS tremor ratings [5; 18; 19; 20; 21; 22].  
The research carried out by [PERSON] _et al._, which enrolled 928 patients, indicated that tremor amplitude is logarithmically correlated to the five-point UPDRS scale [20].  
The Kinesia(tm) system (Great Lakes NeuroTechnologies Inc., Cleveland, OH, USA), which has been approved by the FDA (the United States Food and Drug Administration) for sale, is used to assess parkinsonian symptoms with an inertial measurement unit (IMU), which embeds a three-axis gyroscope and a three-axis accelerometer in a single chip, on the top side of a finger [20]. [PERSON]'s research indicated that the logarithm of the peak powers' summation of power spectrums of both accelerometer and gyroscope signals, during rest and postural tremor tasks, correlated best with UPDRS tremor scale (the coefficient of determination \(r^{2}\) = 0.9) [23]. At the same time, the RMS summation of both accelerometer and gyroscope signals, during action tremor tasks, correlated best with UPDRS tremor ratings (\(r^{2}\) = 0.69) [21].  
In addition, [PERSON] _et al._ presented a glove system to quantitatively assess parkinsonian tremor based on accelerometers [18]. [PERSON] _et al._ presented an ambulatory tremor monitor with a three-axis gyroscope on the wrist [4]. The Motus Movement Monitor (Motus Bioengineering Inc., Benicia, CA, USA), based on a three-axis gyroscope on the top side of the patient's palm, is used to assess tremor and other symptoms [24]. [PERSON] _et al._ used a wrist module, consists of an accelerometer and a gyroscope, to classify and qualitatively assess tremors [25]. [PERSON] _et al._ presented a wearable accelerometer system to classify tremors based on several algorithms, especially the non-linear radial basis function kernel [26]. [PERSON] _et al._ developed an accelerometer sensing system that adopted the short-time Fourier transform to reduce the instability of the tremor signals [27].  
Beginning in August 2014, the Michael J. Fox Foundation for Parkinson's Research (MJFF) and Intel Corporation have joined forces to improve [PERSON]'s disease monitoring via big data analytics and data from wearable computing. Open-access sensor data (accelerometer, compass, _etc._) are available now [28].