Leslie Mahler

Intensive voice treatment (LSVT®LOUD) for Parkinson's disease following deep brain stimulation of the subthalamic nucleus.

PURPOSE Intensive voice therapy (LSVT(®)LOUD) can effectively manage voice and speech symptoms associated with idiopathic Parkinson disease (PD). This small-group study evaluated voice and speech in individuals with and without deep brain stimulation of the subthalamic nucleus (STN-DBS) before and after LSVT LOUD, to determine whether outcomes for surgical subjects were comparable to non-surgical cohorts. METHODS Eight subjects with PD (four with STN-DBS and four without) received LSVT LOUD four times a week for four weeks. Four additional subjects with PD remained untreated. Voice intensity (SPL), Vowel Articulation Index (VAI), the Voice Handicap Index (VHI), and a structured interview were evaluated before and after treatment and again six months later. RESULTS Both treated groups showed significant increases in SPL from pre to post and six-month follow up. VAI was significantly higher for the treated groups compared to the untreated subjects at follow up. Several treated individuals had significant clinical improvement in VHI scores, particularly within the LSVT-DBS group. Treated individuals reported improvements in voice and speech in structured interviews; however, answers suggest more variable long-term maintenance within the LSVT-DBS group. The untreated group exhibited no significant changes in any measure throughout the study. CONCLUSIONS Results support LSVT LOUD for treating voice and speech in individuals with PD following STN-DBS surgery. However, modifications may be required to maintain functional improvements. LEARNING OUTCOMES As a result of this activity, the participant will be able to (1) describe how deep brain stimulation of the subthalamic nucleus may affect voice and speech in Parkinson disease; (2) describe the effects of intensive voice therapy (LSVT(®)LOUD) on people with PD both with and without STN-DBS; (3) describe how individuals with STN-DBS maintained treatment effects over time.

Intensive Treatment of Dysarthria Secondary to Stroke.

This study investigated the impact of a well-defined behavioral dysarthria treatment on acoustic and perceptual measures of speech in four adults with dysarthria secondary to stroke. A single-subject A–B–A experimental design was used to measure the effects of the Lee Silverman Voice Treatment (LSVT® LOUD) on the speech of individual participants. Dependent measures included vocal sound pressure level, phonatory stability, vowel space area, and listener ratings of speech, voice and intelligibility. Statistically significant improvements (p  <  0.05) in vocal dB SPL and phonatory stability as well as larger vowel space area were present for all participants. Listener ratings suggested improved voice quality and more natural speech post-treatment. Speech intelligibility scores improved for one of four participants. These data suggest that people with dysarthria secondary to stroke can respond positively to intensive speech treatments such as LSVT. Further studies are needed to investigate speech treatments specific to stroke.

Evidence-based treatment of voice and speech disorders in Parkinson disease.

Purpose of review Voice and speech impairments are present in nearly 90% of people with Parkinson disease and negatively impact communication and quality of life. This review addresses the efficacy of Lee Silverman Voice Treatment (LSVT) LOUD to improve vocal loudness (as measured by vocal sound pressure level vocSPL) and functional communication in people with Parkinson disease. The underlying physiologic mechanisms of Parkinson disease associated with voice and speech changes and the strength of the current treatment evidence are discussed with recommendations for best clinical practice. Recent findings Two randomized control trials demonstrated that participants who received LSVT LOUD were significantly better on the primary outcome variable of improved vocSPL posttreatment than alternative and no treatment groups. Treatment effects were maintained for up to 2 years. In addition, improvements have been demonstrated in associated outcome variables, including speech rate, monotone, voice quality, speech intelligibility, vocal fold adduction, swallowing, facial expression and neural activation. Advances in technology-supported treatment delivery are enhancing treatment accessibility. Summary Data support the efficacy of LSVT LOUD to increase vocal loudness and functional communication in people with Parkinson disease. Timely intervention is essential for maximizing quality of life for people with Parkinson disease.

Fit: A Fog Computing Device for Speech Tele-Treatments

There is an increasing demand for smart fog-computing gateways as the size of cloud data is growing. This paper presents a Fog computing interface (FIT) for processing clinical speech data. FIT builds upon our previous work on EchoWear, a wearable technology that validated the use of smartwatches for collecting clinical speech data from patients with Parkinsons disease (PD). The fog interface is a low-power embedded system that acts as a smart interface between the smartwatch and the cloud. It collects, stores, and processes the speech data before sending speech features to secure cloud storage. We developed and validated a working prototype of FIT that enabled remote processing of clinical speech data to get speech clinical features such as loudness, short-time energy, zero-crossing rate, and spectral centroid. We used speech data from six patients with PD in their homes for validating FIT. Our results showed the efficacy of FIT as a Fog interface to translate the clinical speech processing chain (CLIP) from a cloud-based backend to a fog-based smart gateway.

A multi-smartwatch system for assessing speech characteristics of people with dysarthria in group settings

Speech-language pathologists (SLPs) frequently use vocal exercises in the treatment of patients with speech disorders. Patients receive treatment in a clinical setting and need to practice outside of the clinical setting to generalize speech goals to functional communication. In this paper, we describe the development of technology that captures mixed speech signals in a group setting and allows the SLP to analyze the speech signals relative to treatment goals. The mixed speech signals are blindly separated into individual signals that are preprocessed before computation of loudness, pitch, shimmer, jitter, semitone standard deviation and sharpness. The proposed method has been previously validated on data obtained from clinical trials of people with Parkinson disease and healthy controls.

Fog Computing in Medical Internet-of-Things: Architecture, Implementation, and Applications

In the era when the market segment of Internet of Things (IoT) tops the chart in various business reports, it is apparently envisioned that the field of medicine expects to gain a large benefit from the explosion of wearables and internet-connected sensors that surround us to acquire and communicate unprecedented data on symptoms, medication, food intake, and daily-life activities impacting ones health and wellness. However, IoT-driven healthcare would have to overcome many barriers, such as: 1) There is an increasing demand for data storage on cloud servers where the analysis of the medical big data becomes increasingly complex, 2) The data, when communicated, are vulnerable to security and privacy issues, 3) The communication of the continuously collected data is not only costly but also energy hungry, 4) Operating and maintaining the sensors directly from the cloud servers are non-trial tasks. This book chapter defined Fog Computing in the context of medical IoT. Conceptually, Fog Computing is a service-oriented intermediate layer in IoT, providing the interfaces between the sensors and cloud servers for facilitating connectivity, data transfer, and queryable local database. The centerpiece of Fog computing is a low-power, intelligent, wireless, embedded computing node that carries out signal conditioning and data analytics on raw data collected from wearables or other medical sensors and offers efficient means to serve telehealth interventions. We implemented and tested an fog computing system using the Intel Edison and Raspberry Pi that allows acquisition, computing, storage and communication of the various medical data such as pathological speech data of individuals with speech disorders, Phonocardiogram (PCG) signal for heart rate estimation, and Electrocardiogram (ECG)-based Q, R, S detection.

Intensive treatment of dysarthria in two adults with Down syndrome

Objective: This study investigated the impact of an established behavioural dysarthria treatment on acoustic and perceptual measures of speech in two adults with Down syndrome (DS) and dysarthria to obtain preliminary measures of treatment effect, effect size and treatment feasibility. Methods: A single-subject A-B-A experimental design was used to measure the effects of the Lee Silverman Voice treatment (LSVT®) on speech in two adults with DS and dysarthria. Dependent measures included vocal sound pressure level (dB SPL), phonatory stability and listener intelligibility scores. Results: Statistically significant improvements (p < 0.05) in vocal dB SPL and phonatory stability were present following treatment in both participants. Speech intelligibility scores improved in one of the two participants. Conclusions: These data suggest that people with DS and dysarthria can respond positively to intensive speech treatment such as LSVT. Further investigations are needed to develop speech treatments specific to DS.

Impact of a Program of Tai Chi Plus Behaviorally Based Dietary Weight Loss on Physical Functioning and Coronary Heart Disease Risk Factors: A Community-Based Study in Obese Older Women

This study employed a quasi-experimental design in a community-based study translating the results of our recent findings on the combined effects of Tai Chi and weight loss on physical function and coronary heart disease (CHD) risk factors. A 16-week intervention was conducted to assess the impact of Tai Chi plus a behavioral weight loss program (TCWL, n = 29) on obese (body mass index [BMI] = 35.4 ± 0.8 kg/m2) older (68.2 ± 1.5 yr.) women compared to a control group (CON, n = 9, BMI = 38.0 ± 1.5 kg/m2, 65.6 ± 2.7 yr.), which was asked to maintain their normal lifestyle. The TCWL group lost weight (1.6 ± 2.9 kg, P = 0.006) while the CON group did not (1.2 ± 1.9 kg, P = 0.106). Physical functioning as measured by the short physical performance battery improved in TCWL when compared to the CON group (β = 1.94, 95% Confidence Interval [CI]: 1.12, 2.76, P < 0.001). TCWL also improved in sit-and-reach flexibility (β = −2.27, 95% CI: −4.09, −0.46, P = 0.016), body fat mass (BMI, β = −0.65, 95% CI: −1.03, −0.26, P = 0.002), waist circumference (β = −1.78, 95% CI: −2.83, −0.72, P = 0.002), systolic blood pressure (β = −16.41, 95% CI: −21.35, −11.48, P < 0.001), and diastolic blood pressure (β = −9.52, 95% CI: −12.65, −6.39, P < 0.001). Thus, TCWL intervention may represent an effective strategy to improve physical function and ameliorate CHD risk in the older adult population.

Effects of respiratory muscle training (RMT) in children with infantile-onset Pompe disease and respiratory muscle weakness

PURPOSE Respiratory muscle weakness is a primary therapeutic challenge for patients with infantile Pompe disease. We previously described the clinical implementation of a respiratory muscle training (RMT) regimen in two adults with late-onset Pompe disease; both demonstrated marked increases in inspiratory and expiratory muscle strength in response to RMT. However, the use of RMT in pediatric survivors of infantile Pompe disease has not been previously reported. METHOD We report the effects of an intensive RMT program on maximum inspiratory pressure (MIP) and maximum expiratory pressure (MEP) using A-B-A (baseline-treatment-posttest) single subject experimental design in two pediatric survivors of infantile Pompe disease. Both subjects had persistent respiratory muscle weakness despite long-term treatment with alglucosidase alfa. RESULTS Subject 1 demonstrated negligible to modest increases in MIP/MEP (6% increase in MIP, d=0.25; 19% increase in MEP, d=0.87), while Subject 2 demonstrated very large increases in MIP/MEP (45% increase in MIP, d=2.38; 81% increase in MEP, d=4.31). Following three-month RMT withdrawal, both subjects maintained these strength increases and demonstrated maximal MIP and MEP values at follow-up. CONCLUSION Intensive RMT may be a beneficial treatment for respiratory muscle weakness in pediatric survivors of infantile Pompe disease.

The Combined Effects of Tai Chi, Resistance Training, and Diet on Physical Function and Body Composition in Obese Older Women

Obesity is a major health problem in the USA, especially in minority populations over the age of 60 years, and the aging process can cause adverse effects on physical function. Previous research has shown that Tai Chi, resistance training (RT), and diet result in overall health improvements. However, the combination of these specific interventions has yet to be translated to obese older women in an urban setting. The purpose of this study was to examine a combined intervention on the primary outcomes of physical function and body composition. Using a nonrandomized design, 26 obese women (65.2 ± 8.1 years) completed a 12-week intervention; participants were assigned to an intervention (EXD) group or a control (CON) group. The EXD group (n = 17) participated in Tai Chi, RT, and a dietary session. The CON group (n = 9) was asked to continue their normal lifestyle. Timed up and go (TUG) time was reduced by 0.64 ± 2.1 seconds (P = 0.04) in the EXD group while the CON group saw a borderline significant increase of 0.71 sec (P = 0.051). The combined intervention helped improve performance on TUG time, but there were no significant increases in other body composition or function measures.