title: Motion Sensors to Assess and Monitor Medical and Surgical Management of Parkinson Disease.
abstract: Patients with Parkinson disease (PD) often suffer from a resting tremor, bradykinesia, rigidity, postural instability, and gait difficulty. Determining a patient's candidacy for deep-brain stimulation (DBS) surgery and tracking their clinical response postoperatively requires that the frequency, duration, and severity of these symptoms be characterized in detail. Conventional means of assessing these symptoms, however, rely heavily on patient self-reporting, which often fails to provide the necessary level of detail. Wearable accelerometers are a novel tool that can detect and objectively characterize these movement abnormalities in both the clinical setting and the patient's home environment. In this article, we review the role of accelerometers in surgical candidate selection, recording and predicting falls, recording and predicting freezing of gait, evaluating surgical outcomes, and evaluating postoperative recovery and in altering DBS settings. Although accelerometry has yet to make it into the mainstream clinic, there is great promise for this technology in monitoring Parkinson patients.
authors.affiliation: New York University Department of Neurosurgery, New York, NY, USA; Cerebrovascular Laboratory, Columbia University, New York, NY, USA.
authors.forename: Bryan
authors.initials: B
authors.lastname: Lieber
authors.affiliation: Department of Neurosurgery, Columbia University, New York, NY, USA; Cerebrovascular Laboratory, Columbia University, New York, NY, USA; College of Physicians and Surgeons, Columbia University, New York, NY, USA. Electronic address: bet2110@cumc.columbia.edu.
authors.forename: Blake E S
authors.initials: BE
authors.lastname: Taylor
authors.affiliation: Department of Neurosurgery, Columbia University, New York, NY, USA; Cerebrovascular Laboratory, Columbia University, New York, NY, USA.
authors.forename: Geoff
authors.initials: G
authors.lastname: Appelboom
authors.affiliation: Department of Neurosurgery, Columbia University, New York, NY, USA.
authors.forename: Guy
authors.initials: G
authors.lastname: McKhann
authors.affiliation: Department of Neurosurgery, Columbia University, New York, NY, USA; Neurointensive Care Unit, Columbia University, New York, NY, USA; Cerebrovascular Laboratory, Columbia University, New York, NY, USA.
authors.forename: E Sander
authors.initials: ES
authors.lastname: Connolly
mesh_terms: D061725:Accelerometry / Q000295:instrumentation* / Q000379:methods*; D000058:Accidental Falls / Q000517:prevention & control / Q000706:statistics & numerical data; D040421:Cell Phone; D046690:Deep Brain Stimulation / Q000379:methods*; D004867:Equipment Design; D005684:Gait / Q000502:physiology; D006801:Humans; D063731:Mobile Applications; D009048:Motor Skills; D010300:Parkinson Disease / Q000175:diagnosis* / Q000503:physiopathology / Q000601:surgery*; D018579:Patient Selection; D045042:Pedunculopontine Tegmental Nucleus / Q000503:physiopathology / Q000601:surgery; D011183:Postoperative Complications / Q000175:diagnosis* / Q000503:physiopathology; D011379:Prognosis; D018570:Risk Assessment / Q000706:statistics & numerical data; D016896:Treatment Outcome
keywords: Accelerometer; Activity tracking; Connected devices; Deep brain stimulation; Monitoring; Movement disorders; Parkinson disease