Apparatus and method for treating neurological disorders

Abstract

An apparatus for treating neurological disorders comprising at least one electrode implantable in a patient's brain and a processing and stimulation device connected to the at least one electrode. The processing and stimulation device comprises at least one stimulation module adapted to generate a stimulation signal characterised by a plurality of parameters; at least one acquisition module adapted to acquire a signal characteristic of cerebral activity and determine its power in at least one frequency band; and at least one control module of at least one parameter of the stimulation signal as a function of the power of the signal characteristic of cerebral activity acquired, based on a transfer function having a saturating trend, wherein the transfer function is configured to set the at least one parameter of the stimulation signal differently dependent on a plurality of power ranges, by keeping the parameter within a predetermined stimulation range.

Claims

1. An apparatus (10) for treating neurological disorders comprising: at least one electrode (12) implantable in the brain of a patient and a processing and stimulation device (14) connected to the at least one electrode (12), wherein the processing and stimulation device (14) comprises: at least one stimulation module (16) adapted to generate a stimulation signal (V.sub.stim) to be sent to the at least one electrode (12), the stimulation signal (V.sub.stim) being characterised by a plurality of parameters (V.sub.a,V.sub.d,V.sub.f), at least one acquisition module (18) of a signal characteristic of cerebral activity coming from the brain of the patient adapted to determine its power (P.sub.BF) in at least one frequency band (BF), and; at least one control module (20) of at least one parameter (V.sub.a,V.sub.d,V.sub.f) of the stimulation signal (V.sub.stim) as a function of the power (P.sub.BF) of the signal characteristic of cerebral activity acquired, based on a transfer function having a saturating trend, wherein the transfer function is such as to set said at least one parameter (V.sub.a,V.sub.d,V.sub.f) of the stimulation signal (V.sub.stim) differently dependent on a plurality of power ranges by keeping the at least one parameter (V.sub.a,V.sub.d,V.sub.f) within a predetermined stimulation range ([V.sub.i_HighThreshold;V.sub.i_LowThreshold]) with i =a,d,f, wherein the transfer function with the saturating trend based on a plurality of power ranges is a piecewise function, placing the stimulation parameter equal to a first value (V.sub.i2) of the stimulation parameter for powers of the signal acquired above a first power limit value and placing the stimulation parameter equal to a second value (V.sub.i1) of the stimulation parameter for powers of the signal acquired below a second power limit value according to the following law: $\mathrm{sat}\left(U\left(P_{\mathrm{BF}}\right)\right)=\{\begin{array}{cc}{V}_{i2}& \mathrm{per}{P}_{\mathrm{BF}}{P}_{\mathrm{BF}2}\\ U_i\left(P_{\mathrm{BF}}\right)& \mathrm{per}{P}_{\mathrm{BF}2}>P_{\mathrm{BF}}>P_{\mathrm{BF}1}\\ V_{i1}& \mathrm{per}{P}_{\mathrm{BF}}{P}_{\mathrm{BF}1}\end{array}$ with V.sub.i1 and V.sub.i2 alternatively set equal to the minimum value V.sub.i_LowThreshold and to the maximum value V.sub.i_HighThreshold of a stimulation parameter V.sub.i, P.sub.BF2 and P.sub.BF1 equal, respectively, to a maximum limit value and a minimum limit value of the saturation ranges of the stimulation parameter V.sub.i and U.sub.i(P.sub.BF) being a law of variability of the stimulation parameter V.sub.i outside the saturation ranges.

2. The apparatus (10) for treating neurological disorders according to claim 1, wherein the law of variability (U.sub.i(P.sub.BF)) of the stimulation parameter (V.sub.i) outside the saturation ranges is of the following type: $U_i\left(P_{\mathrm{BF}}\right)=K_{1i}\frac{V_{i2}-V_{i1}}{P_{\mathrm{BF}2}-P_{\mathrm{BF}1}}\left(P_{\mathrm{BF}}-P_{\mathrm{BF}1}\right)+V_{i1}.$

3. The apparatus (10) for treating neurological disorders according to claim 2, wherein the law of variability (U.sub.i(P.sub.BF)) of the stimulation parameter (V.sub.i) outside the saturation ranges comprises a further additional term (K.sub.2i), thereby resulting in: $U_i\left(P_{\mathrm{BF}}\right)=K_{1i}\frac{V_{i2}-V_{i1}}{P_{\mathrm{BF}2}-P_{\mathrm{BF}1}}\left(P_{\mathrm{BF}}-P_{\mathrm{BF}1}\right)+V_{i1}+K_{2i}.$

4. The apparatus (10) for treating neurological disorders according to claim 1, wherein the law of variability (U.sub.i(P.sub.BF)) of the stimulation parameter (V.sub.i) outside of the saturation ranges is of the following type: $U_i\left(P_{\mathrm{BF}}\right)=K_{1i}\left(V_{i2}-V_{i1}\right)*\left(\frac{1}{1+e^{-p\left(P_{\mathrm{BF}}-\frac{P_{\mathrm{BF}2}-P_{\mathrm{BF}1}}{2}\right)}}\right)+V_{i1}.$

5. The apparatus (10) for treating neurological disorders according to claim 4, wherein the law of variability (U.sub.i(P.sub.BF)) of the stimulation parameter (V.sub.i) outside the saturation ranges comprises a further additional term (K.sub.2i), thereby resulting in: $U_i\left(P_{\mathrm{BF}}\right)=K_{1i}\left(V_{i2}-V_{i1}\right)*\left(\frac{1}{1+e^{-p\left(P_{\mathrm{BF}}-\frac{P_{\mathrm{BF}2}-P_{\mathrm{BF}1}}{2}\right)}}\right)+V_{i1}+K_{2i}.$

6. The apparatus (10) for treating neurological disorders according to claim 1, wherein the at least one acquisition module (18) comprises a processor for transforming the acquired signal characteristic of cerebral activity in the frequency domain, preferably of the type implementing a Fast Fourier Transform.

7. The apparatus (10) for treating neurological disorders according to claim 1, wherein the at least one acquisition module (18) comprises an integral block and/or a derivative block for signal conditioning of the recorded signal characteristic of cerebral activity.

8. The apparatus (10) for treating neurological disorders according to claim 1, wherein the at least one stimulation module (16) is a pulse generator generating a stimulation signal (V.sub.stim) comprising a pulse train, wherein at least one stimulating parameter (V.sub.a,V.sub.d,V.sub.f) of the plurality of stimulating parameters (V.sub.a,V.sub.d,V.sub.f) characterising the stimulation signal (V.sub.stim) is selected from the group consisting of: The amplitude of the stimulation pulses; The stimulation pulse repetition frequency; The stimulation pulse duration.

9. The apparatus for treating neurological disorders according to claim 1, wherein the frequency band (BF) is a sub-band of the beta band (10- 35 Hz) or a sub- band of the low frequencies (4-10 Hz).

10. A method (100) for treating neurological disorders comprising the steps of: acquiring (130) at least one signal characteristic of cerebral activity coming from the brain of the patient and determining the power (P.sub.BF) in at least one frequency band (BF); and adjusting (140) at least one parameter (V.sub.a,V.sub.d,V.sub.f) of the stimulation signal (V.sub.stim) as a function of the power (P.sub.BF) of the signal characteristic of cerebral activity acquired, based on a transfer function having a saturating trend, wherein the transfer function is such as to set said at least one parameter (V.sub.a,V.sub.d,V.sub.f) of the stimulation signal (V.sub.stim) differently dependent on a plurality of power ranges, by keeping the at least one parameter (V.sub.a,V.sub.d,V.sub.f) within a predetermined stimulation range ([V.sub.i_HighThreshold;V.sub.i_LowThreshold]) with i =a,d,f, wherein the transfer function with the saturating trend based on a plurality of power ranges is a piecewise function, setting the stimulation parameter equal to a first value (V.sub.i1) of the stimulation parameter for powers of the signal acquired above a first power limit value and setting the stimulation parameter equal to a second value (V.sub.i2) of the stimulation parameter for powers of the signal acquired below a second power limit value according to the following law: $\mathrm{sat}\left(U\left(P_{\mathrm{BF}}\right)\right)=\{\begin{array}{cc}{V}_{i2}& \mathrm{per}{P}_{\mathrm{BF}}{P}_{\mathrm{BF}2}\\ U_i\left(P_{\mathrm{BF}}\right)& \mathrm{per}{P}_{\mathrm{BF}2}>P_{\mathrm{BF}}>P_{\mathrm{BF}1}\\ V_{i1}& \mathrm{per}{P}_{\mathrm{BF}}{P}_{\mathrm{BF}1}\end{array}$ with V.sub.i1 and V.sub.i2 alternatively set respectively equal to the minimum value V.sub.i_LowThreshold and to the maximum value V.sub.i_HighThreshold of a stimulation parameter V.sub.i, P.sub.BF2 and P.sub.BF1 equal, respectively to a maximum limit value and a minimum limit value of the saturation ranges of the stimulation parameter V.sub.i and U.sub.i (P.sub.BF) being a law of variability of the stimulation parameter V.sub.i outside the saturation ranges.

11. The method (100) for treating neurological disorders according to claim 10, wherein the law of variability (U.sub.i(P.sub.BF)) of the stimulation parameter (V.sub.i) outside the saturation ranges is of the following type: $U_i\left(P_{\mathrm{BF}}\right)=K_{1i}\frac{V_{i2}-V_{i1}}{P_{\mathrm{BF}2}-P_{\mathrm{BF}1}}\left(P_{\mathrm{BF}}-P_{\mathrm{BF}1}\right)+V_i.$

12. The method (100) for treating neurological disorders according to claim 11, wherein the law of variability (U.sub.i(P.sub.BF)) of the stimulation parameter (V.sub.i) outside the saturation ranges comprises a further additional term (K.sub.2i), thereby resulting in: $U_i\left(P_{\mathrm{BF}}\right)=K_{1i}\frac{V_{i2}-V_{i1}}{P_{\mathrm{BF}2}-P_{\mathrm{BF}1}}\left(P_{\mathrm{BF}}-P_{\mathrm{BF}1}\right)+V_{i1}+K_{2i}.$

13. The method (100) for treating neurological disorders according to claim 10, wherein the law of variability (U.sub.i(P.sub.BF)) of the stimulation parameter (V.sub.i) outside the saturation ranges is of the following type: $U_i\left(P_{\mathrm{BF}}\right)=K_{1i}\left(V_{i2}-V_{i1}\right)*\left(\frac{1}{1+e^{-p\left(P_{\mathrm{BF}}-\frac{P_{\mathrm{BF}2}-P_{\mathrm{BF}1}}{2}\right)}}\right)+V_{i1}.$

14. The method (100) for treating neurological disorders according to claim 13, wherein the law of variability (U.sub.i(P.sub.BF)) of the stimulation parameter (V.sub.i) outside the saturation ranges comprises a further additional term (K.sub.2i), thereby resulting in: $U_i\left(P_{\mathrm{BF}}\right)=K_{1i}\left(V_{i2}-V_{i1}\right)*\left(\frac{1}{1+e^{-p\left(P_{\mathrm{BF}}-\frac{P_{\mathrm{BF}2}-P_{\mathrm{BF}1}}{2}\right)}}\right)+V_{i1}+K_{2i}.$

15. The method (100) for treating neurological disorders according to claim 10, wherein the stimulation signal (V.sub.stim) comprises a train of pulses and the stimulation parameter (V.sub.a,V.sub.d,V.sub.f) is selected from the group consisting of: The amplitude of the stimulation pulses; The stimulation pulse repetition frequency; The stimulation pulse duration.

16. The method (100) for treating neurological disorders according to claim 10, wherein the frequency band (BF) and the parameters of the law of variability are obtained according to the following steps: a) identifying (111) at least one maximum threshold value (V.sub.i_HighThreshold) of a stimulation parameter (V.sub.i) beyond which the patient shows signs of actual side effects induced by the stimulation and a minimum threshold value (V.sub.i_LowThreshold) for which the patient shows the minimum or zero benefit induced by stimulation, and setting the extremes of said predetermined stimulation range ([V.sub.i2;V.sub.i1]) alternatively and respectively equal to the threshold values (V.sub.i_HighThreshold) and (V.sub.i_LowThreshold) of the stimulation parameter (V.sub.i) or to a percentage thereof; b) determining (112) the frequency band (BF), by detecting a frequency peak of the power spectrum of a signal characteristic of cerebral activity of the patient recorded in the absence of stimulation, the frequency band (BF) being centered on such a frequency peak and having a bandwidth selected arbitrarily; c) recording (113) the variation over time of the spectral power (P.sub.BF) of a signal characteristic of cerebral activity calculated in the frequency band (BF) in three conditions: base state; active stimulation at the maximum threshold stimulation parameter (V.sub.i_HighThreshold) and pharmacological therapy absent; and active stimulation at the maximum threshold stimulation parameter (V.sub.i_HighThreshold) and pharmacological therapy administered and active; d) identifying (114) a maximum spectral power value (P.sub.BF2) and a minimum spectral power value (P.sub.BFI) of the variation recorded in step c).

17. The method (100) for treating neurological disorders according to claim 16, wherein the maximum spectral power value (P.sub.BF2) of the signal characteristic of cerebral activity calculated in the frequency band (BF) corresponds to a spectral power value (P.sub.OFFOFF) able to be determined when the patient is in the base state and the minimum spectral power value (P.sub.BF1) corresponds to a spectral power value (P.sub.ONON) able to be determined when the patient undergoes both a pharmacological therapy and an active stimulation therapy at the maximum threshold value (V.sub.i_HighThreshold) of the stimulation parameter.

18. The method (100) for treating neurological disorders according to claim 17, wherein the frequency band (BF) is a sub-band of the beta band (10 - 35 Hz).

19. The method (100) for treating neurological disorders according to claim 18, wherein the minimum spectral power (P.sub.BF1) of the signal characteristic of cerebral activity calculated in the frequency band (BF) corresponds to a spectral power value (P.sub.OFFOFF) able to be determined when the patient is in the base state and the maximum spectral power value (P.sub.BF2) corresponds to the spectral power value (P.sub.ONON) able to be determined when the patient undergoes both a pharmacological therapy and an active stimulation therapy at the maximum threshold value (V.sub.i_HighThreshold) of the stimulation parameter.

20. The method (100) for treating neurological disorders according to claim 19, wherein the frequency band (BF) is a sub-band of the low frequencies (4-10 Hz).

Description

(1) Further characteristics and advantages of the present invention will become clearer from the following detailed description of some preferred embodiments thereof, made with reference to the attached drawings.

(2) The different characteristics in the single configurations can be combined with each other as desired according to the previous description, if it were necessary to have advantages resulting specifically from a particular combination.

(3) In such drawings,

(4) FIG. 1 is a schematic representation of an apparatus for treating neurological disorders according to a preferred embodiment of the present invention;

(5) FIG. 2 is a block diagram of the main steps of the method for treating neurological disorders in accordance with the present invention;

(6) FIG. 3 is a detailed block diagram of a step of the method for treating neurological disorders according to the present invention;

(7) FIG. 4a is a diagram of the variation in power in beta band during the calibration step of the maximum and minimum spectral power thresholds in the case of Parkinson's disease;

(8) FIG. 4b is a diagram of the variation in spectral power at the low frequencies during the calibration step of the maximum and minimum spectral power thresholds in the case of Parkinson's disease.

(9) In the following description, to illustrate the figures identical reference numerals or symbols are used to indicate constructive elements with the same function. Moreover, for the sake of clarity of illustration, some references are not repeated in all of the figures.

(10) With reference to FIG. 1, an apparatus for treating neurological disorders is shown, wholly indicated with 10.

(11) The apparatus for treating neurological disorders 10 comprises at least one electro-catheter 11 suitable for being implanted in the brain of a patient to administer an electric stimulation. The electro-catheter 11 preferably comprises at least three metallic contacts accessible through external connections also called electrodes 12. However, it is obviously possible to hypothesise alternative solutions in which the electrodes are not necessarily carried by one same electro-catheter.

(12) The electrodes 12 are connected to a processing and stimulation device 14 that, in the embodiment illustrated in FIG. 1, comprises three functional modules connected together in feedback and interoperating: a stimulation module 16, an acquisition module 18 and a control module 20.

(13) The stimulation module 16 is adapted to generate a stimulation signal V.sub.stim characterised by a set of parameters V.sub.a, V.sub.d, V.sub.f, and to send to the electrodes 12 the stimulation signal generated. In particular, the stimulation module 16 is a generator of pulses defined by the amplitude, frequency and duration of the pulses.

(14) The acquisition module 18 is assigned to the acquisition of a signal characteristic of cerebral activity coming from the brain of the patient. In detail, the acquisition module 18 comprises processing means for transforming the acquired signal characteristic of cerebral activity in the frequency domain. Specifically, the processing means carry out an FFT (Fast Fourier Transform) and can be made through hardware means and/or software means. The acquisition module 18 also preferably comprises an integral block and a derivative block (not illustrated) of the signal characteristic of cerebral activity transformed in the frequency domain.

(15) The control module 20 implements an adjuster, preferably a feedback controller. As illustrated more clearly in FIG. 3, the control module 20 is functionally connected, upstream, to the acquisition module 18 and, downstream, to the stimulation module 16 that determines the stimulation signal V.sub.stim. As a function of the spectral power of the signal characteristic of cerebral activity acquired by the acquisition module 18, the control module 20 determines at least one signal based on which at least one parameter V.sub.a, V.sub.d, V.sub.f of the stimulation signal V.sub.stim set by the stimulation module 16 is defined.

(16) Advantageously, the control module 20 receives in input the signal acquired in the time domain or transformed in the frequency domain by the acquisition module 18 to determine its power. Based on such a power, preferably integrated based on a time constant and/or derived according to specificities of the stimulation parameter to be adjusted, the stimulation parameters are calculated based on a transfer function having a saturating trend such as to also determine that the stimulation parameters are variable between two saturation values (V.sub.i_HighThreshold; V.sub.i_LowThreshold) between which the stimulation is actually effective.

(17) In particular, the transfer function having a saturating trend is implemented as a piecewise function based on ranges of values of the input power, i.e. such as to place the stimulation parameter V.sub.i equal to a maximum value V.sub.i_HighThreshold or to a minimum value V.sub.i_LowThreshold in the saturation ranges, allowing the stimulation parameter V.sub.i to vary, outside the saturation ranges, as a function of the power P.sub.BF of the signal acquired according to a law of variability U.sub.i(P.sub.BF).

(18) This translates into the following transfer function, where the saturation ranges correspond to powers P.sub.BF of the acquired signal greater than a first power limit value P.sub.BF2 or powers P.sub.BF of the acquired signal below a second power limit value P.sub.BF1:

(19) $\mathrm{sat}\left(U\left(P_{\mathrm{BF}}\right)\right)=\{\begin{array}{cc}{V}_{i2}& \mathrm{per}{P}_{\mathrm{BF}}{P}_{\mathrm{BF}2}\\ U_i\left(P_{\mathrm{BF}}\right)& \mathrm{per}{P}_{\mathrm{BF}2}>P_{\mathrm{BF}}>P_{\mathrm{BF}1}\\ V_{i1}& \mathrm{per}{P}_{\mathrm{BF}}{P}_{\mathrm{BF}1}\end{array}.$

(20) In particular, the law of variability U.sub.i(P.sub.BF) of the stimulation parameter outside the saturation ranges is of the following type:

(21) $U_i\left(P_{\mathrm{BF}}\right)=K_{1i}\frac{V_{i2}-V_{i1}}{P_{\mathrm{BF}2}-P_{\mathrm{BF}1}}\left(P_{\mathrm{BF}}-P_{\mathrm{BF}1}\right)+V_{i1}+K_{2i}.$

(22) Alternatively, the law of variability U.sub.i(P.sub.BF) of the stimulation parameter outside of the saturation ranges is of the sigmoid type:

(23) $U_i\left(P_{\mathrm{BF}}\right)=K_{1i}\left(V_{i2}-V_{i1}\right)*\left(\frac{1}{1+e^{-p\left(P_{\mathrm{BF}}-\frac{P_{\mathrm{BF}2}-P_{\mathrm{BF}1}}{2}\right)}}\right)+V_{i1}+K_{2i}.$

(24) In both cases, the parameter K.sub.1i represents a proportional adjustment factor preferably having unitary value so that the maximum excursion of P.sub.BF corresponds to the maximum excursion of the output V.sub.i(P.sub.BF). In the case in which the parameter K.sub.1i takes on values greater than 1, an additional saturation block is foreseen in order to ensure that the stimulation parameter V.sub.i is kept within the predetermined stimulation range. In the sole case of sigmoid function, the parameter p is adjusted based on the desired value of the function U.sub.i(P.sub.BF) around the point P.sub.BF2 and P.sub.BF1.

(25) Specifically, since deep brain stimulation uses a stimulus defined by three stimulation parameters V.sub.a, V.sub.d, V.sub.f relative, respectively, to amplitude, duration and frequency of the stimulation signal V.sub.stim, the control module 20 foresees to implement a respective law of variability V.sub.a(P.sub.BF),V.sub.d(P.sub.BF),V.sub.f(P.sub.BF) for each stimulation parameter V.sub.a, V.sub.d, V.sub.f. The stimulation signal V.sub.stim in output from the stimulation module 16 is characterised by the parameters V.sub.a, V.sub.d, V.sub.f, calculated based on the respective output of the control module 20.

(26) Advantageously, the time constant based on which the integration of the spectral power P.sub.BF takes place, is selected as a function of the control requirements: the greater the time constant the smaller the variance on the evaluation of the spectral power P.sub.BF of the acquired signal and therefore on the instantaneous clinical state of the patient. However, increasing the time constant increases the delay in identifying the clinical state of the patient.

(27) Preferably, the control allows variable setting of the time constant , so that the most suitable time constant can be set each time based on the specific application, taking into account the compromise between speed and accuracy of detection of the power.

(28) The adjuster implemented by the control module 20 is characterised by a wide degree of flexibility thanks to the possibility of calibrating the adjustment parameters K.sub.1i, K.sub.2i P.sub.BF2, P.sub.BF1, , V.sub.i1, V.sub.i2. It is thus possible to carry out a vast range of adjustment strategies.

(29) The operating method 100 of the apparatus for treating neurological disorders 10 is schematically illustrated in FIG. 2.

(30) Prior to the stimulation treatment there is an initialisation session (step 110). The initialisation session is carried out after the patient has spent a sufficient time (generally 12 hours) without pharmacological medication. After such a time period without pharmacological therapy, the patient is considered to be in the so-called OFF-OFF or base clinical condition, i.e. in the absence of stimulation and with effect of pharmacological therapy having worn off.

(31) Then there is the identification (step 111) of at least one of the threshold values of the specific stimulation parameters of the patient based on which to set the treatment. In particular, in simplifying terms, the amplitude of the stimulation voltage is identified.

(32) Such identification takes place through an expert, like for example a neurologist specialised in the treatment of neurological disorders through deep brain stimulation. The step of identifying the parameters (step 111) therefore takes place through a series of stimulation tests with different parameter values, based on which the expert decides the maximum threshold value V.sub.i_HighThreshold, to obtain the maximum clinical effect before the appearance of side effects, and minimum threshold value V.sub.i_LowThreshold, to obtain the minimum or zero clinical effect. The saturation values of the stimulation parameters V.sub.i2 and V.sub.i1 can be placed equal, respectively, to the maximum threshold value V.sub.i_HighThreshold and minimum threshold value V.sub.i_LowThreshold or alternatively, respectively equal to the minimum threshold value V.sub.i_LowThreshold and maximum threshold value V.sub.i_HighThreshold.

(33) In the case in which the parameter analysed is the amplitude V.sub.a of the stimulation signal V.sub.stim, the step of identifying the stimulation parameters leads to determining the maximum and minimum amplitude of the voltage that can be set V.sub.a_HighThreshold and V.sub.a_LowThreshold. Similarly, the maximum/minimum frequency and/or the maximum/minimum duration of the stimulation signal V.sub.stim can be identified.

(34) Then there is a recording (step 112) of the neurophysiological signal: the harmonic content of the neurophysiological signal of the specific patient in the absence of stimulation is detected and analysed to identify the characteristics of the specific frequency spectrum of the patient. In particular, at least one frequency peak is identified, with respect to which the at least one frequency band BF is centred based on which to calculate the spectral power of the signal. The frequency bands are defined through a minimum frequency and a maximum frequency: fw_min<BF<fw_max and correspond to the frequency bands with which the symptoms of the neurological disorders that it is wished to counteract most probably correlate. The frequencies fw_min and fw_max can be selected arbitrarily.

(35) Once the stimulation parameters and the frequency band have been defined, there is a calibration step (step 113) in which the signal characteristic of cerebral activity is recorded in a plurality of different conditions to extract the values of the power in the frequency band defined previously. Specifically, for the calibration step (step 113), the neurophysiological signal of the patient at the base state is detected, i.e. in the absence of therapies of any kind (pharmacological or stimulation) also called OFF-OFF state, and the power in the band of interest is stored. The recording of the neurophysiological signal at the OFF-OFF state takes place for an initial period, in general equal to 20 minutes. Once the initial period has ended, the stimulation is brought to the maximum threshold stimulation values V.sub.i_HighThreshold determined previously. The processing and stimulation device proceeds to store the power of the signal characteristic of cerebral activity of the patient in the clinical OFF-ON state, i.e. in the absence of pharmacological therapy (LEVOdopamine), but in the presence of stimulation. After a further time period, in general equal to another 20 minutes, the pharmacological therapy is started again proceeding to store the power. After a third time period, the drug taken is considered to be completely assimilated and the patient is in the clinical ON-ON state, i.e. in the presence of pharmacological therapy and of stimulation. The storage of the power of the signal characteristic of cerebral activity of the patient is therefore ended.

(36) Once the storage has ended, in the three initialisation steps 110, of the power calculated in the frequency band identified initially, the maximum power value P.sub.BF2 and minimum power value P.sub.BF1 are extrapolated.

(37) In the specific case illustrated in FIG. 4a, relative to a frequency band of interest coinciding with a sub-band of the beta band (10-35 Hz), the maximum power value P.sub.BF2 coincides with the power value in the OFF-OFF state (P.sub.OFFOFF), whereas the minimum power value P.sub.BF1 coincides with the power value in the ON-ON state (P.sub.ONON).

(38) In example terms, the case is also shown in which the frequency band of interest coincides with the low frequencies (4-10 Hz). In this case, as shown in FIG. 4b, the minimum power value P.sub.BF1 coincides with the power value in the OFF-OFF state (P.sub.lowOFFOFF) whereas the maximum power value P.sub.BF2 coincides with the power value at the ON-ON state (P.sub.lowONON).

(39) Once the initialisation step 110 of the therapy has ended, the method 100 for treating neurological disorders comprises the repetition of the following steps.

(40) The delivery of the deep brain stimulation is started (step 120).

(41) Thereafter (step 130), the acquisition module 18 records a signal characteristic of cerebral activity of the patient (sub-step 131), preferably the local field potentials LFP recorded at the grey nucleus, and thereafter transforms it (sub-step 132) preferably in the frequency domain, for example through FFT (Fast Fourier Transform), determining its spectral power P.sub.BF (sub-step 133). Preferably, the power is also integrated based on the time constant (sub-step 134).

(42) Finally, based on the spectral power P.sub.BF recorded, there is a step of updating the stimulation parameters (step 140).

(43) For this purpose, the control module 20 preferably compares the power P.sub.BF with a range of reference values [P.sub.BF2; P.sub.BF1] that correlate more with the frequency band of interest. Based on the difference between the power P.sub.BF calculated and the lower limit P.sub.BF1 of such a reference range [P.sub.BF2; P.sub.BF1] a control signal for a stimulation module (16) is generated which sets the stimulation parameters (V.sub.a, V.sub.d, V.sub.f) according to the law of variability V.sub.i(P.sub.BF) given above.

(44) In the case in which the frequency band of interest coincides with a sub-band of the beta band (10-35 Hz) that, as will be seen hereinafter, proves particularly suitable for the treatment of some symptoms of Parkinson's disease, the upper extreme P.sub.BF2 of the range of values is equal to the power P.sub.OFFOFF at the OFF-OFF state and the lower extreme P.sub.BF1 of the range of values is equal to the power P.sub.ONON at the ON-ON state determined in the initialisation step, with P.sub.BF2>P.sub.BF1.

(45) In example terms, the case is now discussed in which the treatment method according to the invention is specifically used for treating clinical-motor functions of Parkinson's disease that most correlate with the beta band , which has therefore been identified as the reference frequency band BF based on which to calculate the spectral power of the acquired local field potentials. For this treatment it has also proven sufficient to carry out an adaptation of just the stimulation amplitude V.sub.a.

(46) In this case, the law of variability takes the form:

(47) $U_i\left(P_{\mathrm{BF}}\right)=K_{1i}\frac{V_{i2}-V_{i1}}{P_{\mathrm{BF}2}-P_{\mathrm{BF}1}}\left(P_{\mathrm{BF}}-P_{\mathrm{BF}1}\right)+V_{i1}+K_{2i}$

(48) With the adjustment parameters K.sub.1i, P.sub.BF2, P.sub.BF1, V.sub.i1, V.sub.i2, K.sub.2i equal to: P.sub.BF=P.sub.; P.sub.BF2=P.sub.OFFOFF P.sub.BF1=P.sub.ONON V.sub.i2=V.sub.a_HighThreshold V.sub.i1=V.sub.a_LowThreshold K.sub.1i=K.sub.a=1 K.sub.2i=0

(49) In the case of the treatment of the symptoms of Parkinson's disease that correlate with the beta band, there is therefore a simplified adjustment model based on the following law of variability:

(50) 0$V_a\left(P_{}\right)=\mathrm{sat}\left(P_{}\right)=\{\begin{array}{cc}{V}_{\mathrm{a\_HighThreshold}}& \mathrm{per}{P}_{}{P}_{\mathrm{OFFOFF}}\\ \frac{\begin{array}{c}{V}_{\mathrm{a\_HighThreshold}}-\\ V_{\mathrm{a\_LowThreshold}}\end{array}}{\begin{array}{c}{P}_{\mathrm{OFFOFF}}-\\ P_{\mathrm{ONON}}\end{array}}\left(P_{}-P_{\mathrm{ONON}}\right)+V_{\mathrm{a\_LowThreshold}}& \mathrm{per}{P}_{\mathrm{OFFOFF}}>P_{}>P_{\mathrm{ONON}}\\ V_{\mathrm{a\_LowThreshold}}& \mathrm{per}{P}_{}{P}_{\mathrm{ONON}}\end{array}$

(51) Alternatively, the case is now discussed in which the treatment method according to the invention is specifically used for the treatment of the clinical-motor fluctuations of Parkinson's disease that most correlate with the band of low frequencies (4-10 Hz), which has therefore been identified as reference frequency band BF based on which to calculate the spectral power of the acquired local field potentials. For this treatment, it also proved sufficient to carry out an adaptation of just the stimulation amplitude V.sub.a.

(52) In this case, the law of variability takes the form

(53) $U_i\left(P_{\mathrm{BF}}\right)=K_{1i}\frac{V_{i2-}{V}_{i1}}{P_{\mathrm{BF}2}-P_{\mathrm{BF}1}}\left(P_{\mathrm{BF}2}-P_{\mathrm{BF}}\right)+V_{i1}+K_{2i}.$

(54) With the adjustment parameters K.sub.1i, P.sub.BF2, P.sub.BF1, V.sub.i1, V.sub.i2, K.sub.2i equal to: P.sub.BF=P.sub.low P.sub.BF2=P.sub.lowONON P.sub.BF1=P.sub.lowOFFOFF V.sub.i2=V.sub.a_LowThreshold V.sub.i1=V.sub.a_HighThreshold K.sub.1i=K.sub.a=1 K.sub.2i=0

(55) In the case of treatment of the symptoms of Parkinson's disease that correlate most with the low frequencies, there is therefore a simplified adjustment model defined by the following law of variability:

(56) $V_a\left(P_{\mathrm{low}}\right)=\mathrm{sat}\left(P_{\mathrm{low}}\right)=\{\begin{array}{cc}{V}_{a_{\mathrm{LowThreshold}}}& \mathrm{per}{P}_{\mathrm{low}}{P}_{\mathrm{lowONON}}\\ \frac{\begin{array}{c}{V}_{a_{\mathrm{LowThreshold}}}-\\ V_{a_{\mathrm{HighThreshold}}}\end{array}}{\begin{array}{c}{P}_{\mathrm{lowONON}-}\\ P_{\mathrm{lowOFFOFF}}\end{array}}\left(P_{\mathrm{low}}-P_{\mathrm{lowOFFOFF}}\right)+V_{a_{\mathrm{HighThreshold}}}& \mathrm{per}{P}_{\mathrm{lowOFFOFF}}>P_{\mathrm{low}}>P_{\mathrm{lowONON}}\\ V_{a_{\mathrm{HighThreshold}}}& \mathrm{per}{P}_{\mathrm{low}}{P}_{\mathrm{lowOFFOFF}}\end{array}$

(57) From the description that has been made the characteristics of the apparatus and of the method for treating neurological disorders object of the present invention are clear, just as the relative advantages are also clear.

(58) From the embodiments described above further variants are possible, without departing from the teaching of the invention.

(59) Finally, it is clear that an apparatus and a method for treating neurological disorders thus conceived can undergo numerous modifications and variants, all of which are covered by the invention; moreover, all of the details can be replaced by technically equivalent elements. In practice, the materials used, as well as the sizes, can be whatever according to the technical requirements.