Development of an Assessment Method of Forearm Pronation/Supination Motor Function based on Mobile Phone Accelerometer Data for an Early Diagnosis of Parkinson's Disease

@inproceedings{Choi2016DevelopmentOA,
  title={Development of an Assessment Method of Forearm Pronation/Supination Motor Function based on Mobile Phone Accelerometer Data for an Early Diagnosis of Parkinson's Disease},
  author={Ji Hun Choi and Hyeo-Il Ma and Yun Joong Kim and Unjoo Lee},
  year={2016}
}
A series of forearm pronation and supination motor tasks (FPSMT) has been developed to quantitatively assess various primary motor symptoms such as resting tremor, bradykinesia, rigidity, and posture disturbance using an accelerometer built into a smartphone, which is portable, comfortable and cost-effective. The FPSMT has two series of tasks, Flat and Up, which differ according to initial forearm posture. The results from 33 subjects including 6 PD patients showed sensitivities and… 
View via Publisher
sersc.org
6 Citations
Background Citations
1
Methods Citations
2

Figures and Tables from this paper

6 Citations

The detection of hand tremor through the characteristics of finger movement while typing

Typing data was analysed and it was showed that hand tremor in PD can be detected from keystroke features and the diagnosis of early PD through typing can achieve the clinical requirement of at least two cardinal features being present (bradykinesia and tremor).

High-accuracy detection of early Parkinson's Disease using multiple characteristics of finger movement while typing

Keystroke timing information was captured as subjects typed on a computer keyboard over an extended period and showed that PD affects various characteristics of hand and finger movement and that these can be detected.

A Smart Inertial System for 24h Monitoring and Classification of Tremor and Freezing of Gait in Parkinson’s Disease

The main objective of this study is the realization of advanced methods of automatic evaluation and continuous monitoring tools for the support to the medical evaluation of Parkinson’s disease (PD)…

Parkinson’s Disease Detection by Using Machine Learning Algorithms and Hand Movement Signal from LeapMotion Sensor

This work is devoted to the detection of Parkinson’s disease (PD) by the kinematic parameters of hand movements using machine learning methods. Hand movements of PD patients (N16) and control group…

Keyboard typing for the detection of early Parkinson's disease

Technologies Assessing Limb Bradykinesia in Parkinson’s Disease

This review provides an up-to-date repository and synthesis of the current literature regarding technology used for assessing limb bradykinesia in PD and discusses the current trends with regards to technology.

References

SHOWING 1-10 OF 32 REFERENCES

Quantitative Assessment of Forearm Pronation/Supination Motor functions using a Smartphone Accelerometer for an early Diagnosis of Parkinson’s Disease

The FPSMT has two procedures of tasks, “Flat” and “Up” according to the initial forearm postures, and the result from thirty three subjects including six PD patients showed reasonable sensitivities and specificities.

Development of an acquisition and visualization of forearm tremors and pronation/supination motor activities in a smartphone based environment for an early diagnosis of Parkinson's disease

An application ProSupino was designed for android mobile phones and to collect in real-time forearm movement data from the tri-axial accelerometer while a subject develops with one of two series of…

Smartphone-based evaluation of parkinsonian hand tremor: Quantitative measurements vs clinical assessment scores

  • Nikolaos KostikisD. Hristu-VarsakelisMarianthi ArnaoutoglouChristos Kotsavasiloglou
  • Medicine
    2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
  • 2014
This work compares quantitative measurements of hand tremor in twenty-three Parkinson's disease patients, with their clinical scores in theHand tremor components of the Unified Parkinson's Disease Rating Scale (UPDRS), which is considered the “gold standard” in the clinical assessment of the disease.

Validity and Responsiveness of At-Home Touch Screen Assessments in Advanced Parkinson's Disease

Correlations between OTS and clinical rating scales were adequate indicating that the test battery contains important elements of the information of well-established scales, and responsiveness and reproducibility were better for OTS than for total UPDRS.

High accuracy discrimination of Parkinson's disease participants from healthy controls using smartphones

This study objectively measure and quantify key movement severity symptoms of Parkinson's disease using consumer-grade smartphones with in-built accelerometers, and extracts a range of different features based on the time and frequency-domain properties of the acceleration time series.

Quantitative measurement of motor symptoms in Parkinson's disease: A study with full-body motion capture data

The experimental results indicate that the quantitative measure on spatio-temporal statistics learnt from the motion capture data reveal distinctive differences between mild and severe symptoms.

Monitoring Motor Fluctuations in Patients With Parkinson's Disease Using Wearable Sensors

This paper presents the results of a pilot study to assess the feasibility of using accelerometer data to estimate the severity of symptoms and motor complications in patients with Parkinson's…

Quantitative wearable sensors for objective assessment of Parkinson's disease

This review discusses promising wearable technology, addresses which parameters should be prioritized in such assessment strategies, and reports about studies that have already investigated daily life issues in PD using this new technology.

High‐resolution tracking of motor disorders in Parkinson's disease during unconstrained activity

The initial findings indicate that new sensor technology and software algorithms can be effective in enhancing wearable sensor‐based system performance for monitoring PD motor disorders during unconstrained activities.

Inertial Sensing to Determine Movement Disorder Motion Present before and after Treatment

The results show that inertial sensors can be used to differentiate between effectivelymedicated PD motion and control motion; such a differentiation can often be difficult to perform with the human eye because effectively medicated PD patients tend to not produce much tremor.