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Vocal markers of motor, cognitive, and depressive symptoms in Parkinson's disease

机译：帕金森氏病的运动，认知和抑郁症状的声音标记

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Patients with Parkinson's disease (PD) often suffer from cognitive impairment and depression in addition to motor dysfunction. These non-motor symptoms may be challenging to diagnose and disentangle from the effects of motor impairment. Analysis of vocal acoustics may improve detection and differentiation of motor, cognitive, and depressive symptom domains simultaneously. Certain vocal markers may be distinctly correlated with specific symptom domains, while other vocal markers may overlap across domains. In this paper, a joint multi-domain characterization of PD symptoms is presented. Speech recordings from 35 PD patients were analyzed for speech markers characterizing articulatory coordination based on resonant (formant) frequencies and delta-mel cepstral coefficients (dMFCC), as well as phonemic timing based on phoneme-dependent speaking rates. Moderate correlations were found between vocal markers and the motor and cognitive symptoms of PD, and weaker correlations with depressive symptoms. Notable differences were identified in the correlation patterns for each symptom domain. Of particular interest, the durations of certain phonemes were correlated with cognitive compared with motor symptom severity. Statistical models, developed based on the vocal markers, achieved moderate accuracy in predicting motor severity (r=0.42) and global cognition (r=0.52) but not depression (r=-0.21). This work suggests it may be possible to distinguish the impact of non-motor PD symptoms on speech. Future study is warranted to further develop symptom-specific vocal marker models in PD.
机译：帕金森氏病（PD）的患者除运动功能障碍外，还经常患有认知障碍和抑郁症。这些非运动症状可能难以诊断和摆脱运动障碍的影响。对声音的声学分析可以同时改善运动，认知和抑郁症状域的检测和区分。某些声音标记可能与特定症状域明显相关，而其他声音标记可能跨域重叠。在本文中，提出了PD症状的联合多域表征。分析了来自35位PD患者的语音记录，以表征基于共振（共振峰）频率和Δmel倒谱系数（dMFCC）以及基于音素相关语音速率的音素定时的发音协调特征的语音标记。声音标记与PD的运动和认知症状之间存在中等相关性，而与抑郁症状之间的相关性较弱。在每个症状域的相关模式中发现了显着差异。特别令人感兴趣的是，与运动症状严重程度相比，某些音素的持续时间与认知相关。基于语音标记开发的统计模型在预测运动严重度（r = 0.42）和整体认知（r = 0.52）时达到了中等准确度，但在抑郁症（r = -0.21）方面没有达到预期。这项工作表明，可能有可能区分非运动性PD症状对言语的影响。有必要进行进一步的研究，以进一步开发PD中特定于症状的声音标记模型。

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