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Connection

Jeffrey Hausdorff to Wearable Electronic Devices

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This is a "connection" page, showing publications Jeffrey Hausdorff has written about Wearable Electronic Devices.
Jeffrey Hausdorff
Connection Strength
6.249
Wearable Electronic Devices
  1. Daily-Living Freezing of Gait as Quantified Using Wearables in People With Parkinson Disease: Comparison With Self-Report and Provocation Tests. Phys Ther. 2022 12 06; 102(12).
    View in: PubMed
    Score: 0.795
  2. Automatic Quantification of Tandem Walking Using a Wearable Device: New Insights Into Dynamic Balance and Mobility in Older Adults. J Gerontol A Biol Sci Med Sci. 2021 01 01; 76(1):101-107.
    View in: PubMed
    Score: 0.696
  3. Body-Worn Sensors for Remote Monitoring of Parkinson's Disease Motor Symptoms: Vision, State of the Art, and Challenges Ahead. J Parkinsons Dis. 2021; 11(s1):S35-S47.
    View in: PubMed
    Score: 0.696
  4. Using Wearable Sensors and Machine Learning to Automatically Detect Freezing of Gait during a FOG-Provoking Test. Sensors (Basel). 2020 Aug 10; 20(16).
    View in: PubMed
    Score: 0.677
  5. A wearable sensor identifies alterations in community ambulation in multiple sclerosis: contributors to real-world gait quality and physical activity. J Neurol. 2020 Jul; 267(7):1912-1921.
    View in: PubMed
    Score: 0.658
  6. Using wearables to assess bradykinesia and rigidity in patients with Parkinson's disease: a focused, narrative review of the literature. J Neural Transm (Vienna). 2019 06; 126(6):699-710.
    View in: PubMed
    Score: 0.622
  7. The transition between turning and sitting in patients with Parkinson's disease: A wearable device detects an unexpected sequence of events. Gait Posture. 2019 01; 67:224-229.
    View in: PubMed
    Score: 0.598
  8. Distributional data analysis via quantile functions and its application to modeling digital biomarkers of gait in Alzheimer's Disease. Biostatistics. 2023 Jul 14; 24(3):539-561.
    View in: PubMed
    Score: 0.207
  9. Postural control and gait measures derived from wearable inertial measurement unit devices in Huntington's disease: Recommendations for clinical outcomes. Clin Biomech (Bristol, Avon). 2022 06; 96:105658.
    View in: PubMed
    Score: 0.191
  10. Technical validation of real-world monitoring of gait: a multicentric observational study. BMJ Open. 2021 12 02; 11(12):e050785.
    View in: PubMed
    Score: 0.185
  11. Different Combinations of Mobility Metrics Derived From a Wearable Sensor Are Associated With Distinct Health Outcomes in Older Adults. J Gerontol A Biol Sci Med Sci. 2020 05 22; 75(6):1176-1183.
    View in: PubMed
    Score: 0.167
  12. What happens before the first step? A New Approach to Quantifying Gait Initiation Using a Wearable Sensor. Gait Posture. 2020 02; 76:128-135.
    View in: PubMed
    Score: 0.161
  13. Quantitative mobility metrics from a wearable sensor predict incident parkinsonism in older adults. Parkinsonism Relat Disord. 2019 08; 65:190-196.
    View in: PubMed
    Score: 0.156
  14. The Parkinson's disease e-diary: Developing a clinical and research tool for the digital age. Mov Disord. 2019 05; 34(5):676-681.
    View in: PubMed
    Score: 0.154
  15. A roadmap for implementation of patient-centered digital outcome measures in Parkinson's disease obtained using mobile health technologies. Mov Disord. 2019 05; 34(5):657-663.
    View in: PubMed
    Score: 0.154
  16. Real-Time Constant Monitoring of Fall Risk Index by Means of Fully-Wireless Insoles. Stud Health Technol Inform. 2017; 237:193-197.
    View in: PubMed
    Score: 0.132
Connection Strength

The connection strength for concepts is the sum of the scores for each matching publication.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.