Table 1 Mean and standard deviation of energy difference values in mechanomyogram frequency band and types between age-matched healthy controls and patients with Parkinson’s disease.

From: Application of high-sensitivity acceleration sensor detecting micro-mechanomyogram and deep learning for Parkinson’s disease classification

No.

MMG frequency band

Participant

Mean (± SD)

×10−6[(m/s2) 2]

Statistical result

1

Low-MMG [5–15 Hz]

HC

8.89 (± 7.23)

< two-way repeated measures ANOVA>

{HC, PD}: p < 0.05*,

{Low-MMG, Micro-MMG}: p < 0.001***,

{HC, PD} × {Low-MMG, Micro-MMG}: p < 0.01**.

< Multiple comparisons using Shaffer’s method>

{HC, PD} at Low-MMG: p < 0.01**

{HC, PD} at Micro-MMG: p < 0.001***

{Low-MMG, Micro-MMG} for HC: p < 0.001***

{Low-MMG, Micro-MMG} for PD: p < 0.001***

2

 

PD

15.48 (± 20.21)

3

Micro-MMG [15–35 Hz]

HC

1.96 (± 2.40)

4

 

PD

0.78 (± 1.00)

  1. ANOVA, analysis of variance; HC, healthy controls; MMG, mechanomyogram; PD, Parkinson’s disease; SD, standard deviation*: p < 0.05, **: p < 0.01, ***: p < 0.001.
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